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Shic F, Barney EC, Naples AJ, Dommer KJ, Chang SA, Li B, McAllister T, Atyabi A, Wang Q, Bernier R, Dawson G, Dziura J, Faja S, Jeste SS, Murias M, Johnson SP, Sabatos-DeVito M, Helleman G, Senturk D, Sugar CA, Webb SJ, McPartland JC, Chawarska K. The Selective Social Attention task in children with autism spectrum disorder: Results from the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) feasibility study. Autism Res 2023; 16:2150-2159. [PMID: 37749934 PMCID: PMC11003770 DOI: 10.1002/aur.3026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 08/25/2023] [Indexed: 09/27/2023]
Abstract
The Selective Social Attention (SSA) task is a brief eye-tracking task involving experimental conditions varying along socio-communicative axes. Traditionally the SSA has been used to probe socially-specific attentional patterns in infants and toddlers who develop autism spectrum disorder (ASD). This current work extends these findings to preschool and school-age children. Children 4- to 12-years-old with ASD (N = 23) and a typically-developing comparison group (TD; N = 25) completed the SSA task as well as standardized clinical assessments. Linear mixed models examined group and condition effects on two outcome variables: percent of time spent looking at the scene relative to scene presentation time (%Valid), and percent of time looking at the face relative to time spent looking at the scene (%Face). Age and IQ were included as covariates. Outcome variables' relationships to clinical data were assessed via correlation analysis. The ASD group, compared to the TD group, looked less at the scene and focused less on the actress' face during the most socially-engaging experimental conditions. Additionally, within the ASD group, %Face negatively correlated with SRS total T-scores with a particularly strong negative correlation with the Autistic Mannerism subscale T-score. These results highlight the extensibility of the SSA to older children with ASD, including replication of between-group differences previously seen in infants and toddlers, as well as its ability to capture meaningful clinical variation within the autism spectrum across a wide developmental span inclusive of preschool and school-aged children. The properties suggest that the SSA may have broad potential as a biomarker for ASD.
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Affiliation(s)
- Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children’s Research Institute, Seattle, Washington, USA
- Department of General Pediatrics, University of Washington School of Medicine, Seattle, Washington, USA
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Erin C. Barney
- Center for Child Health, Behavior and Development, Seattle Children’s Research Institute, Seattle, Washington, USA
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Adam J. Naples
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Kelsey J. Dommer
- Center for Child Health, Behavior and Development, Seattle Children’s Research Institute, Seattle, Washington, USA
| | - Shou An Chang
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Beibin Li
- Center for Child Health, Behavior and Development, Seattle Children’s Research Institute, Seattle, Washington, USA
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
- Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, Washington, USA
| | - Takumi McAllister
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Adham Atyabi
- Department of General Pediatrics, University of Washington School of Medicine, Seattle, Washington, USA
- Department of Computer Science, University of Colorado - Colorado Springs, Colorado Springs, Colorado, USA
| | - Quan Wang
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
- Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, China
| | - Raphael Bernier
- Department of Psychiatry & Behavioral Science, University of Washington School of Medicine, Seattle, Washington, USA
| | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina, USA
| | - James Dziura
- Emergency Medicine, Yale University, New Haven, Connecticut, USA
| | - Susan Faja
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
- Department of Pediatrics, Boston Children’s Hospital, Boston, Massachusetts, USA
| | - Shafali Spurling Jeste
- Department of Psychiatry & Biobehavioral Sciences, University of California Los Angeles, Los Angeles, California, USA
- Department of Neurology, Keck School of Medicine of USC, Los Angeles, California, USA
- Division of Neurology, Children’s Hospital Los Angeles, Los Angeles, California, USA
| | - Michael Murias
- Department of Medical Social Sciences, Northwestern University, Evanston, Illinois, USA
| | - Scott P. Johnson
- Department of Psychology, University of California Los Angeles, Los Angeles, California, USA
| | - Maura Sabatos-DeVito
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina, USA
| | - Gerhard Helleman
- Department of Psychiatry & Biobehavioral Sciences, University of California Los Angeles, Los Angeles, California, USA
- Department of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Damla Senturk
- Department of Biostatistics, University of California Los Angeles, Los Angeles, California, USA
| | - Catherine A. Sugar
- Department of Biostatistics, University of California Los Angeles, Los Angeles, California, USA
| | - Sara Jane Webb
- Department of General Pediatrics, University of Washington School of Medicine, Seattle, Washington, USA
- Department of Psychiatry & Behavioral Science, University of Washington School of Medicine, Seattle, Washington, USA
| | - James C. McPartland
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Katarzyna Chawarska
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
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2
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Finn CE, Han GT, Naples AJ, Wolf JM, McPartland JC. Development of peak alpha frequency reflects a distinct trajectory of neural maturation in autistic children. Autism Res 2023; 16:2077-2089. [PMID: 37638733 DOI: 10.1002/aur.3017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Accepted: 08/05/2023] [Indexed: 08/29/2023]
Abstract
Electroencephalographic peak alpha frequency (PAF) is a marker of neural maturation that increases with age throughout childhood. Distinct maturation of PAF is observed in children with autism spectrum disorder such that PAF does not increase with age and is instead positively associated with cognitive ability. The current study clarifies and extends previous findings by characterizing the effects of age and cognitive ability on PAF between diagnostic groups in a sample of children and adolescents with and without autism spectrum disorder. Resting EEG data and behavioral measures were collected from 45 autistic children and 34 neurotypical controls aged 8 to 18 years. Utilizing generalized additive models to account for nonlinear relations, we examined differences in the joint effect of age and nonverbal IQ by diagnosis as well as bivariate relations between age, nonverbal IQ, and PAF across diagnostic groups. Age was positively associated with PAF among neurotypical children but not among autistic children. In contrast, nonverbal IQ but not age was positively associated with PAF among autistic children. Models accounting for nonlinear relations revealed different developmental trajectories as a function of age and cognitive ability based on diagnostic status. Results align with prior evidence indicating that typical age-related increases in PAF are absent in autistic children and that PAF instead increases with cognitive ability in these children. Findings suggest the potential of PAF to index distinct trajectories of neural maturation in autistic children.
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Affiliation(s)
- Caroline E Finn
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Gloria T Han
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
- Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Adam J Naples
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Julie M Wolf
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - James C McPartland
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
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3
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Tsang T, Naples AJ, Barney EC, Xie M, Bernier R, Dawson G, Dziura J, Faja S, Jeste SS, McPartland JC, Nelson CA, Murias M, Seow H, Sugar C, Webb SJ, Shic F, Johnson SP. Attention Allocation During Exploration of Visual Arrays in ASD: Results from the ABC-CT Feasibility Study. J Autism Dev Disord 2023; 53:3220-3229. [PMID: 35657448 PMCID: PMC10980886 DOI: 10.1007/s10803-022-05569-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/05/2022] [Indexed: 11/29/2022]
Abstract
Visual exploration paradigms involving object arrays have been used to examine salience of social stimuli such as faces in ASD. Recent work suggests performance on these paradigms may associate with clinical features of ASD. We evaluate metrics from a visual exploration paradigm in 4-to-11-year-old children with ASD (n = 23; 18 males) and typical development (TD; n = 23; 13 males). Presented with arrays containing faces and nonsocial stimuli, children with ASD looked less at (p = 0.002) and showed fewer fixations to (p = 0.022) faces than TD children, and spent less time looking at each object on average (p = 0.004). Attention to the screen and faces correlated positively with social and cognitive skills in the ASD group (ps < .05). This work furthers our understanding of objective measures of visual exploration in ASD and its potential for quantifying features of ASD.
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Affiliation(s)
| | | | - Erin C Barney
- Yale School of Medicine, New Haven, USA
- Seattle Children's Research Institute, 1920 Terry Ave, M/S Cure-3, Seattle, WA, 98101, USA
| | - Minhang Xie
- Seattle Children's Research Institute, 1920 Terry Ave, M/S Cure-3, Seattle, WA, 98101, USA
| | - Raphael Bernier
- Seattle Children's Research Institute, 1920 Terry Ave, M/S Cure-3, Seattle, WA, 98101, USA
- University of Washington, Seattle, USA
| | | | | | - Susan Faja
- Boston Children's Hospital, Boston, USA
- Harvard Medical School, Boston, USA
| | - Shafali Spurling Jeste
- University of California, Los Angeles, USA
- University of Southern California, Los Angeles, CA, USA
| | | | - Charles A Nelson
- Boston Children's Hospital, Boston, USA
- Harvard Medical School, Boston, USA
| | | | | | | | - Sara J Webb
- Seattle Children's Research Institute, 1920 Terry Ave, M/S Cure-3, Seattle, WA, 98101, USA
- University of Washington, Seattle, USA
| | - Frederick Shic
- Seattle Children's Research Institute, 1920 Terry Ave, M/S Cure-3, Seattle, WA, 98101, USA.
- University of Washington, Seattle, USA.
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4
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Faja S, Sabatos-DeVito M, Sridhar A, Kuhn JL, Nikolaeva JI, Sugar CA, Webb SJ, Bernier RA, Sikich L, Hellemann G, Senturk D, Naples AJ, Shic F, Levin AR, Seow HA, Dziura JD, Jeste SS, Chawarska K, Nelson CA, Dawson G, McPartland JC. Evaluation of clinical assessments of social abilities for use in autism clinical trials by the autism biomarkers consortium for clinical trials. Autism Res 2023; 16:981-996. [PMID: 36929131 PMCID: PMC10192100 DOI: 10.1002/aur.2905] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 02/11/2023] [Indexed: 03/18/2023]
Abstract
Clinical trials in autism spectrum disorder (ASD) often rely on clinician rating scales and parent surveys to measure autism-related features and social behaviors. To aid in the selection of these assessments for future clinical trials, the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) directly compared eight common instruments with respect to acquisition rates, sensitivity to group differences, equivalence across demographic sub-groups, convergent validity, and stability over a 6-week period. The sample included 280 children diagnosed with ASD (65 girls) and 119 neurotypical children (36 girls) aged from 6 to 11 years. Full scale IQ for ASD ranged from 60 to 150 and for neurotypical ranged from 86 to 150. Instruments measured clinician global assessment and autism-related behaviors, social communication abilities, adaptive function, and social withdrawal behavior. For each instrument, we examined only the scales that measured social or communication functioning. Data acquisition rates were at least 97.5% at T1 and 95.7% at T2. All scales distinguished diagnostic groups. Some scales significantly differed by participant and/or family demographic characteristics. Within the ASD group, most clinical instruments exhibited weak (≥ |0.1|) to moderate (≥ |0.4|) intercorrelations. Short-term stability was moderate (ICC: 0.5-0.75) to excellent (ICC: >0.9) within the ASD group. Variations in the degree of stability may inform viability for different contexts of use, such as identifying clinical subgroups for trials versus serving as a modifiable clinical outcome. All instruments were evaluated in terms of their advantages and potential concerns for use in clinical trials.
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Affiliation(s)
- Susan Faja
- Department of Pediatrics, Harvard Medical School. Boston MA. USA
- Boston Children’s Hospital. Boston MA. USA
| | - Maura Sabatos-DeVito
- Duke Center for Autism and Brain Development, Duke University. Durham NC. USA
- Department of Psychiatry & Behavioral Sciences, Duke University. Durham NC. USA
| | | | - Jocelyn L. Kuhn
- Department of Pediatrics, Boston University School of Medicine. Boston MA. USA
| | - Julia I. Nikolaeva
- Department of Communication Sciences and Disorders, Northwestern University. Evanston IL. USA
| | - Catherine A. Sugar
- Department of Biostatistics, University of California Los Angeles. Los Angeles CA. USA
- Department of Psychiatry & Biobehavioral Sciences, University of California Los Angeles. Los Angeles CA. USA
| | - Sara Jane Webb
- Center for Child Health, Behavior and Development, Seattle Children’s Research Institute. Seattle WA. USA
- Department of Psychiatry & Behavioral Science, University of Washington School of Medicine. Seattle WA. USA
| | - Raphael A. Bernier
- Department of Psychiatry & Behavioral Science, University of Washington School of Medicine. Seattle WA. USA
| | - Linmarie Sikich
- Department of Psychiatry & Behavioral Sciences, Duke University. Durham NC. USA
| | - Gerhard Hellemann
- Department of Biostatistics, University of Alabama at Birmingham. Birmingham AB. USA
| | - Damla Senturk
- Department of Biostatistics, University of California Los Angeles. Los Angeles CA. USA
| | - Adam J. Naples
- Yale Child Study Center, Yale University. New Haven CT. USA
| | - Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children’s Research Institute. Seattle WA. USA
- Department of General Pediatrics, University of Washington School of Medicine. Seattle WA. USA
| | - April R. Levin
- Department of Neurology, Boston Children’s Hospital. Boston MA. USA
- Harvard Medical School. Boston MA. USA
| | - Helen A. Seow
- Yale Center for Clinical Investigation, Yale University. New Haven CT. USA
| | - James D. Dziura
- Department of Emergency Medicine, Yale University. New Haven CT. USA
| | - Shafali S. Jeste
- Department of Pediatrics and Neurology, Children’s Hospital, Los Angeles. Los Angeles CA. USA
- USC Keck School of Medicine. Los Angeles CA. USA
| | | | - Charles A. Nelson
- Department of Pediatrics, Harvard Medical School. Boston MA. USA
- Boston Children’s Hospital. Boston MA. USA
- Graduate School of Education, Harvard University. Boston MA. USA
| | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Duke University. Durham NC. USA
- Department of Psychiatry & Behavioral Sciences, Duke University. Durham NC. USA
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5
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Shurtz L, Schwartz C, DiStefano C, McPartland JC, Levin AR, Dawson G, Kleinhans NM, Faja S, Webb SJ, Shic F, Naples AJ, Seow H, Bernier RA, Chawarska K, Sugar CA, Dziura J, Senturk D, Santhosh M, Jeste SS. Concomitant medication use in children with autism spectrum disorder: Data from the Autism Biomarkers Consortium for Clinical Trials. Autism 2023; 27:952-966. [PMID: 36086805 PMCID: PMC9995606 DOI: 10.1177/13623613221121425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
LAY ABSTRACT Children with autism spectrum disorder are prescribed a variety of medications that affect the central nervous system (psychotropic medications) to address behavior and mood. In clinical trials, individuals taking concomitant psychotropic medications often are excluded to maintain homogeneity of the sample and prevent contamination of biomarkers or clinical endpoints. However, this choice may significantly diminish the clinical representativeness of the sample. In a recent multisite study designed to identify biomarkers and behavioral endpoints for clinical trials (the Autism Biomarkers Consortium for Clinical Trials), school-age children with autism spectrum disorder were enrolled without excluding for medications, thus providing a unique opportunity to examine characteristics of psychotropic medication use in a research cohort and to guide future decisions on medication-related inclusion criteria. The aims of the current analysis were (1) to quantify the frequency and type of psychotropic medications reported in school-age children enrolled in the ABC-CT and (2) to examine behavioral features of children with autism spectrum disorder based on medication classes. Of the 280 children with autism spectrum disorder in the cohort, 42.5% were taking psychotropic medications, with polypharmacy in half of these children. The most commonly reported psychotropic medications included melatonin, stimulants, selective serotonin reuptake inhibitors, alpha agonists, and antipsychotics. Descriptive analysis showed that children taking antipsychotics displayed a trend toward greater overall impairment. Our findings suggest that exclusion of children taking concomitant psychotropic medications in trials could limit the clinical representativeness of the study population, perhaps even excluding children who may most benefit from new treatment options.
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Affiliation(s)
| | | | | | | | - April R Levin
- Boston Children’s Hospital, USA
- Harvard University, USA
| | | | | | - Susan Faja
- Boston Children’s Hospital, USA
- Harvard University, USA
| | - Sara J Webb
- University of Washington, USA
- Seattle Children’s Research Institute, USA
| | - Frederick Shic
- University of Washington, USA
- Seattle Children’s Research Institute, USA
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6
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Webb SJ, Naples AJ, Levin AR, Hellemann G, Borland H, Benton J, Carlos C, McAllister T, Santhosh M, Seow H, Atyabi A, Bernier R, Chawarska K, Dawson G, Dziura J, Faja S, Jeste S, Murias M, Nelson CA, Sabatos-DeVito M, Senturk D, Shic F, Sugar CA, McPartland JC. The Autism Biomarkers Consortium for Clinical Trials: Initial Evaluation of a Battery of Candidate EEG Biomarkers. Am J Psychiatry 2023; 180:41-49. [PMID: 36000217 PMCID: PMC10027395 DOI: 10.1176/appi.ajp.21050485] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Numerous candidate EEG biomarkers have been put forward for use in clinical research on autism spectrum disorder (ASD), but biomarker development has been hindered by limited attention to the psychometric properties of derived variables, inconsistent results across small studies, and variable methodology. The authors evaluated the basic psychometric properties of a battery of EEG assays for their potential suitability as biomarkers in clinical trials. METHODS This was a large, multisite, naturalistic study in 6- to 11-year-old children who either had an ASD diagnosis (N=280) or were typically developing (N=119). The authors evaluated an EEG battery composed of well-studied assays of resting-state activity, face perception (faces task), biological motion perception, and visual evoked potentials (VEPs). Biomarker psychometrics were evaluated in terms of acquisition rates, construct performance, and 6-week stability. Preliminary evaluation of use was explored through group discrimination and phenotypic correlations. RESULTS Three assays (resting state, faces task, and VEP) show promise in terms of acquisition rates and construct performance. Six-week stability values in the ASD group were moderate (intraclass correlations ≥0.66) for the faces task latency of the P1 and N170, the VEP amplitude of N1 and P1, and resting alpha power. Group discrimination and phenotype correlations were primarily observed for the faces task P1 and N170. CONCLUSIONS In the context of a large-scale, rigorous evaluation of candidate EEG biomarkers for use in ASD clinical trials, neural response to faces emerged as a promising biomarker for continued evaluation. Resting-state activity and VEP yielded mixed results. The study's biological motion perception assay failed to display construct performance. The results provide information about EEG biomarker performance that is relevant for the next stage of biomarker development efforts focused on context of use.
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Affiliation(s)
- Sara Jane Webb
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Adam J Naples
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - April R Levin
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Gerhard Hellemann
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Heather Borland
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Jessica Benton
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Carter Carlos
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Takumi McAllister
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Megha Santhosh
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Helen Seow
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Adham Atyabi
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Raphael Bernier
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Katarzyna Chawarska
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Geraldine Dawson
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - James Dziura
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Susan Faja
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Shafali Jeste
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Michael Murias
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Charles A Nelson
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Maura Sabatos-DeVito
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Damla Senturk
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Frederick Shic
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Catherine A Sugar
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - James C McPartland
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
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Levy EJ, Foss-Feig J, Isenstein EL, Srihari V, Anticevic A, Naples AJ, McPartland JC. Electrophysiological Studies of Reception of Facial Communication in Autism Spectrum Disorder and Schizophrenia. Rev J Autism Dev Disord 2022; 9:521-554. [PMID: 36568688 PMCID: PMC9783109 DOI: 10.1007/s40489-021-00260-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 04/22/2021] [Indexed: 12/30/2022]
Abstract
Autism spectrum disorder (ASD) and schizophrenia spectrum disorders (SZ) are characterized by difficulty with social cognition and atypical reception of facial communication - a key area in the Research Domain Criteria framework. To identify areas of overlap and dissociation between ASD and SZ, we review studies of event-related potentials (ERP) to faces across ASD and SZ populations, focusing on ERPs implicated in social perception: P100, N170, N250, and P300. There were many inconsistent findings across studies; however, replication was strongest for delayed N170 latency in ASD and attenuated N170 amplitude in SZ. These results highlight the challenges of replicating research findings in heterogeneous clinical populations and the need for transdiagnostic research that continuously quantifies behavior and neural activity across neurodevelopmental disorders.
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Affiliation(s)
| | - Jennifer Foss-Feig
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai
- Seaver Autism Center, Icahn School of Medicine at Mount Sinai
| | | | - Vinod Srihari
- Department of Psychiatry, Yale University School of Medicine
| | - Alan Anticevic
- Department of Psychiatry, Yale University School of Medicine
- Department of Psychology, Yale University
- Division of Neurogenetics, Neurocomputation, and Neuroimaging, Yale University School of Medicine
| | - Adam J. Naples
- Yale Child Study Center, Yale University School of Medicine
| | - James C. McPartland
- Department of Psychology, Yale University
- Yale Child Study Center, Yale University School of Medicine
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8
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Naples AJ, Foss-Feig JH, Wolf JM, Srihari VH, McPartland JC. Predictability modulates neural response to eye contact in ASD. Mol Autism 2022; 13:42. [PMID: 36309762 PMCID: PMC9618208 DOI: 10.1186/s13229-022-00519-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 09/26/2022] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Deficits in establishing and maintaining eye-contact are early and persistent vulnerabilities of autism spectrum disorder (ASD), and the neural bases of these deficits remain elusive. A promising hypothesis is that social features of autism may reflect difficulties in making predictions about the social world under conditions of uncertainty. However, no research in ASD has examined how predictability impacts the neural processing of eye-contact in naturalistic interpersonal interactions. METHOD We used eye tracking to facilitate an interactive social simulation wherein onscreen faces would establish eye-contact when the participant looked at them. In Experiment One, receipt of eye-contact was unpredictable; in Experiment Two, receipt of eye-contact was predictable. Neural response to eye-contact was measured via the N170 and P300 event-related potentials (ERPs). Experiment One included 23 ASD and 46 typically developing (TD) adult participants. Experiment Two included 25 ASD and 43 TD adult participants. RESULTS When receipt of eye-contact was unpredictable, individuals with ASD showed increased N170 and increased, but non-specific, P300 responses. The magnitude of the N170 responses correlated with measures of sensory and anxiety symptomology, such that increased response to eye-contact was associated with increased symptomology. However, when receipt of eye-contact was predictable, individuals with ASD, relative to controls, exhibited slower N170s and no differences in the amplitude of N170 or P300. LIMITATIONS Our ASD sample was composed of adults with IQ > 70 and included only four autistic women. Thus, further research is needed to evaluate how these results generalize across the spectrum of age, sex, and cognitive ability. Additionally, as analyses were exploratory, some findings failed to survive false-discovery rate adjustment. CONCLUSIONS Neural response to eye-contact in ASD ranged from attenuated to hypersensitive depending on the predictability of the social context. These findings suggest that the vulnerabilities in eye-contact during social interactions in ASD may arise from differences in anticipation and expectation of eye-contact in addition to the perception of gaze alone.
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Affiliation(s)
- Adam J Naples
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA.
| | - Jennifer H Foss-Feig
- Department of Psychiatry, Mount Sinai Icahn School of Medicine, New York, NY, USA
- Seaver Autism Center for Research and Treatment Mount Sinai Icahn School of Medicine, New York, NY, USA
| | - Julie M Wolf
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Vinod H Srihari
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - James C McPartland
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA.
- Center for Brain and Mind Health, Yale University School of Medicine, New Haven, CT, USA.
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9
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Shic F, Naples AJ, Barney EC, Chang SA, Li B, McAllister T, Kim M, Dommer KJ, Hasselmo S, Atyabi A, Wang Q, Helleman G, Levin AR, Seow H, Bernier R, Charwaska K, Dawson G, Dziura J, Faja S, Jeste SS, Johnson SP, Murias M, Nelson CA, Sabatos-DeVito M, Senturk D, Sugar CA, Webb SJ, McPartland JC. The autism biomarkers consortium for clinical trials: evaluation of a battery of candidate eye-tracking biomarkers for use in autism clinical trials. Mol Autism 2022; 13:15. [PMID: 35313957 PMCID: PMC10124777 DOI: 10.1186/s13229-021-00482-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 12/20/2021] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Eye tracking (ET) is a powerful methodology for studying attentional processes through quantification of eye movements. The precision, usability, and cost-effectiveness of ET render it a promising platform for developing biomarkers for use in clinical trials for autism spectrum disorder (ASD). METHODS The autism biomarkers consortium for clinical trials conducted a multisite, observational study of 6-11-year-old children with ASD (n = 280) and typical development (TD, n = 119). The ET battery included: Activity Monitoring, Social Interactive, Static Social Scenes, Biological Motion Preference, and Pupillary Light Reflex tasks. A priori, gaze to faces in Activity Monitoring, Social Interactive, and Static Social Scenes tasks were aggregated into an Oculomotor Index of Gaze to Human Faces (OMI) as the primary outcome measure. This work reports on fundamental biomarker properties (data acquisition rates, construct validity, six-week stability, group discrimination, and clinical relationships) derived from these assays that serve as a base for subsequent development of clinical trial biomarker applications. RESULTS All tasks exhibited excellent acquisition rates, met expectations for construct validity, had moderate or high six-week stabilities, and highlighted subsets of the ASD group with distinct biomarker performance. Within ASD, higher OMI was associated with increased memory for faces, decreased autism symptom severity, and higher verbal IQ and pragmatic communication skills. LIMITATIONS No specific interventions were administered in this study, limiting information about how ET biomarkers track or predict outcomes in response to treatment. This study did not consider co-occurrence of psychiatric conditions nor specificity in comparison with non-ASD special populations, therefore limiting our understanding of the applicability of outcomes to specific clinical contexts-of-use. Research-grade protocols and equipment were used; further studies are needed to explore deployment in less standardized contexts. CONCLUSIONS All ET tasks met expectations regarding biomarker properties, with strongest performance for tasks associated with attention to human faces and weakest performance associated with biological motion preference. Based on these data, the OMI has been accepted to the FDA's Biomarker Qualification program, providing a path for advancing efforts to develop biomarkers for use in clinical trials.
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Affiliation(s)
- Frederick Shic
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, 1920 Terry Ave, Seattle, WA, 98101, USA.
- Department of General Pediatrics, University of Washington School of Medicine, Seattle, WA, USA.
| | - Adam J Naples
- Yale Child Study Center, Yale University School of Medicine, 230 South Frontage Road, New Haven, CT, 06520, USA
| | - Erin C Barney
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, 1920 Terry Ave, Seattle, WA, 98101, USA
- Yale Child Study Center, Yale University School of Medicine, 230 South Frontage Road, New Haven, CT, 06520, USA
| | - Shou An Chang
- Department of Psychology, Yale University, 2 Hillhouse Ave, New Haven, CT, 06520, USA
| | - Beibin Li
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, 1920 Terry Ave, Seattle, WA, 98101, USA
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA
| | - Takumi McAllister
- Yale Child Study Center, Yale University School of Medicine, 230 South Frontage Road, New Haven, CT, 06520, USA
| | - Minah Kim
- Department of Psychology, University of Virginia, 102 Gilmer Hall, P.O. Box 400400, Charlottesville, VA, 22904, USA
| | - Kelsey J Dommer
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, 1920 Terry Ave, Seattle, WA, 98101, USA
| | - Simone Hasselmo
- Yale Child Study Center, Yale University School of Medicine, 230 South Frontage Road, New Haven, CT, 06520, USA
| | - Adham Atyabi
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, 1920 Terry Ave, Seattle, WA, 98101, USA
- Department of General Pediatrics, University of Washington School of Medicine, Seattle, WA, USA
- Department of Computer Science, University of Colorado - Colorado Springs, Colorado Springs, CO, USA
| | - Quan Wang
- Yale Child Study Center, Yale University School of Medicine, 230 South Frontage Road, New Haven, CT, 06520, USA
| | - Gerhard Helleman
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - April R Levin
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Helen Seow
- Yale Child Study Center, Yale University School of Medicine, 230 South Frontage Road, New Haven, CT, 06520, USA
| | - Raphael Bernier
- Department of Psychiatry and Behavioral Science, University of Washington School of Medicine, Seattle, WA, USA
| | - Katarzyna Charwaska
- Yale Child Study Center, Yale University School of Medicine, 230 South Frontage Road, New Haven, CT, 06520, USA
| | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, USA
| | - James Dziura
- Emergency Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Susan Faja
- Harvard Medical School, Boston, MA, USA
- Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
| | - Shafali Spurling Jeste
- Division of Neurology, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Scott P Johnson
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
| | - Michael Murias
- Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL, USA
| | - Charles A Nelson
- Harvard Medical School, Boston, MA, USA
- Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
- Graduate School of Education, Harvard University, Boston, MA, USA
| | | | - Damla Senturk
- Department of Biostatistics, University of California Los Angeles, Los Angeles, CA, USA
| | - Catherine A Sugar
- Department of Biostatistics, University of California Los Angeles, Los Angeles, CA, USA
- Division of Neurology, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Sara J Webb
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, 1920 Terry Ave, Seattle, WA, 98101, USA
- Department of Psychiatry and Behavioral Science, University of Washington School of Medicine, Seattle, WA, USA
| | - James C McPartland
- Yale Child Study Center, Yale University School of Medicine, 230 South Frontage Road, New Haven, CT, 06520, USA.
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10
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Webb SJ, Emerman I, Sugar C, Senturk D, Naples AJ, Faja S, Benton J, Borland H, Carlos C, Levin AR, McAllister T, Santhosh M, Bernier RA, Chawarska K, Dawson G, Dziura J, Jeste S, Kleinhans N, Murias M, Sabatos-DeVito M, Shic F, McPartland JC. Identifying Age Based Maturation in the ERP Response to Faces in Children With Autism: Implications for Developing Biomarkers for Use in Clinical Trials. Front Psychiatry 2022; 13:841236. [PMID: 35615454 PMCID: PMC9126041 DOI: 10.3389/fpsyt.2022.841236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 03/21/2022] [Indexed: 01/27/2023] Open
Abstract
Recent proposals have suggested the potential for neural biomarkers to improve clinical trial processes in neurodevelopmental conditions; however, few efforts have identified whether chronological age-based adjustments will be necessary (as used in standardized behavioral assessments). Event-related potentials (ERPs) demonstrate early differences in the processing of faces vs. objects in the visual processing system by 4 years of age and age-based improvement (decreases in latency) through adolescence. Additionally, face processing has been proposed to be related to social skills as well as autistic social-communication traits. While previous reports suggest delayed latency in individuals with autism spectrum disorder (ASD), extensive individual and age based heterogeneity exists. In this report, we utilize a sample of 252 children with ASD and 118 children with typical development (TD), to assess the N170 and P100 ERP component latencies (N170L and P100L, respectively), to upright faces, the face specificity effect (difference between face and object processing), and the inversion effect (difference between face upright and inverted processing) in relation to age. First, linear mixed models (LMMs) were fitted with fixed effect of age at testing and random effect of participant, using all available data points to characterize general age-based development in the TD and ASD groups. Second, LMM models using only the TD group were used to calculate age-based residuals in both groups. The purpose of residualization was to assess how much variation in ASD participants could be accounted for by chronological age-related changes. Our data demonstrate that the N170L and P100L responses to upright faces appeared to follow a roughly linear relationship with age. In the ASD group, the distribution of the age-adjusted residual values suggest that ASD participants were more likely to demonstrate slower latencies than would be expected for a TD child of the same age, similar to what has been identified using unadjusted values. Lastly, using age-adjusted values for stratification, we found that children who demonstrated slowed age-adjusted N170L had lower verbal and non-verbal IQ and worse face memory. These data suggest that age must be considered in assessing the N170L and P100L response to upright faces as well, and these adjusted values may be used to stratify children within the autism spectrum.
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Affiliation(s)
- Sara Jane Webb
- Center on Child Health, Behavior, & Development, Seattle Children's Research Institute, Seattle, WA, United States.,Department of Psychiatry & Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
| | - Iris Emerman
- Center on Child Health, Behavior, & Development, Seattle Children's Research Institute, Seattle, WA, United States
| | - Catherine Sugar
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Psychiatry & Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Statistics, University of California, Los Angeles, Los Angeles, CA, United States
| | - Damla Senturk
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Psychiatry & Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Statistics, University of California, Los Angeles, Los Angeles, CA, United States
| | - Adam J Naples
- Yale Child Study Center, Yale University, New Haven, CT, United States
| | - Susan Faja
- Harvard Medical School, Harvard University, Boston, MA, United States.,Department of Neurology, Boston Children's Hospital, Boston, MA, United States
| | - Jessica Benton
- Center on Child Health, Behavior, & Development, Seattle Children's Research Institute, Seattle, WA, United States
| | - Heather Borland
- Center on Child Health, Behavior, & Development, Seattle Children's Research Institute, Seattle, WA, United States
| | - Carter Carlos
- Yale Child Study Center, Yale University, New Haven, CT, United States
| | - April R Levin
- Harvard Medical School, Harvard University, Boston, MA, United States.,Department of Neurology, Boston Children's Hospital, Boston, MA, United States
| | - Takumi McAllister
- Yale Child Study Center, Yale University, New Haven, CT, United States
| | - Megha Santhosh
- Center on Child Health, Behavior, & Development, Seattle Children's Research Institute, Seattle, WA, United States
| | - Raphael A Bernier
- Department of Psychiatry & Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
| | | | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States.,Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC, United States
| | - James Dziura
- Yale Center for Clinical Investigation, Yale University, New Haven, CT, United States
| | - Shafali Jeste
- Department of Psychiatry & Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Neurology, Children's Hospital of Los Angeles, Los Angeles, CA, United States
| | - Natalia Kleinhans
- Center on Human Development and Disabilities, University of Washington, Seattle, WA, United States.,Department of Radiology, University of Washington School of Medicine, Seattle, WA, United States
| | - Michael Murias
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States.,Medical Social Sciences, Northwestern University, Chicago, IL, United States
| | - Maura Sabatos-DeVito
- Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC, United States
| | - Frederick Shic
- Center on Child Health, Behavior, & Development, Seattle Children's Research Institute, Seattle, WA, United States.,Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, United States
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11
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Kala S, Rolison MJ, Trevisan DA, Naples AJ, Pelphrey K, Ventola P, McPartland JC. Brief Report: Preliminary Evidence of the N170 as a Biomarker of Response to Treatment in Autism Spectrum Disorder. Front Psychiatry 2021; 12:709382. [PMID: 34267691 PMCID: PMC8275957 DOI: 10.3389/fpsyt.2021.709382] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 06/02/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by primary difficulties in social function. Individuals with ASD display slowed neural processing of faces, as indexed by the latency of the N170, a face-sensitive event-related potential. Currently, there are no objective biomarkers of ASD useful in clinical care or research. Efficacy of behavioral treatment is currently evaluated through subjective clinical impressions. To explore whether the N170 might have utility as an objective index of treatment response, we examined N170 before and after receipt of an empirically validated behavioral treatment in children with ASD. Method: Electroencephalography (EEG) data were obtained on a preliminary cohort of preschool-aged children with ASD before and after a 16-week course of PRT and in a subset of participants in waitlist control (16-weeks before the start of PRT) and follow-up (16-weeks after the end of PRT). EEG was recorded while participants viewed computer-generated faces with neutral and fearful affect. Results: Significant reductions in N170 latency to faces were observed following 16 weeks of PRT intervention. Change in N170 latency was not observed in the waitlist-control condition. Conclusions: This exploratory study offers suggestive evidence that N170 latency may index response to behavioral treatment. Future, more rigorous, studies in larger samples are indicated to evaluate whether the N170 may be useful as a biomarker of treatment response.
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Affiliation(s)
- Shashwat Kala
- Child Study Center, Yale School of Medicine, New Haven, CT, United States
| | - Max J. Rolison
- Child Study Center, Yale School of Medicine, New Haven, CT, United States
| | | | - Adam J. Naples
- Child Study Center, Yale School of Medicine, New Haven, CT, United States
| | - Kevin Pelphrey
- Department of Neurology, University of Virginia, Charlottesville, VA, United States
| | - Pamela Ventola
- Child Study Center, Yale School of Medicine, New Haven, CT, United States
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12
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Altschuler MR, Trevisan DA, Wolf JM, Naples AJ, Foss-Feig JH, Srihari VH, McPartland JC. Face perception predicts affective theory of mind in autism spectrum disorder but not schizophrenia or typical development. J Abnorm Psychol 2021; 130:413-422. [PMID: 34180705 PMCID: PMC8244155 DOI: 10.1037/abn0000621] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Autism spectrum disorder (ASD) and schizophrenia spectrum disorder (SCZ) have overlapping symptomatology related to difficulties with social cognition. Yet, few studies have directly compared social cognition in ASD, SCZ, and typical development (TD). The current study examined individual differences in face recognition and its relation to affective theory of mind (ToM) in each diagnostic group. Adults with ASD (n = 31), SCZ (n = 43), and TD (n = 47) between the ages of 18 and 48 years-old with full scale IQ above 80 participated in this study. The Reading the Mind in the Eyes Test (RMET) measured affective ToM, and the Benton Facial Recognition Test (BFRT) measured face perception. Adults with ASD and SCZ did not differ in their affective ToM abilities, and both groups showed affective ToM difficulties compared with TD. However, better face recognition ability uniquely predicted better affective ToM ability in ASD. Results suggest that affective ToM difficulties may relate to face processing in ASD but not SCZ. By clarifying the complex nature of individual differences in affective ToM and face recognition difficulties in these disorders, the present study suggests there may be divergent mechanisms underlying pathways to social dysfunction in ASD compared with SCZ. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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Affiliation(s)
| | | | | | | | | | - Vinod H Srihari
- Department of Psychiatry, Yale University School of Medicine
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13
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Parker TC, Crowley MJ, Naples AJ, Rolison MJ, Wu J, Trapani JA, McPartland JC. The N170 event-related potential reflects delayed neural response to faces when visual attention is directed to the eyes in youths with ASD. Autism Res 2021; 14:1347-1356. [PMID: 33749161 DOI: 10.1002/aur.2505] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 03/10/2021] [Accepted: 03/11/2021] [Indexed: 11/10/2022]
Abstract
Atypical neural response to faces is thought to contribute to social deficits in autism spectrum disorder (ASD). Compared to typically developing (TD) controls, individuals with ASD exhibit delayed brain responses to upright faces at a face-sensitive event-related potential (ERP), the N170. Given observed differences in patterns of visual attention to faces, it is not known whether slowed neural processing may simply reflect atypical looking to faces. The present study manipulated visual attention to facial features to examine whether directed attention to the eyes normalizes N170 latency in ASD. ERPs were recorded in 30 children and adolescents with ASD as well as 26 TD children and adolescents. Results replicated prior findings of shorter N170 latency to the eye region of the face in TD individuals. In contrast, those with ASD did not demonstrate modulation of N170 latency by point of regard to the face. Group differences in latency were most pronounced when attention was directed to the eyes. Results suggest that well-replicated findings of N170 delays in ASD do not simply reflect atypical patterns of visual engagement with experimental stimuli. These findings add to a body of evidence indicating that N170 delays are a promising marker of atypical neural response to social information in ASD. LAY SUMMARY: This study looks at how children's and adolescents' brains respond when looking at different parts of a face. Typically developing children and adolescents processed eyes faster than other parts of the face, whereas this pattern was not seen in ASD. Children and adolescents with ASD processed eyes more slowly than typically developing children. These findings suggest that observed inefficiencies in face processing in ASD are not simply reflective of failure to attend to the eyes.
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Affiliation(s)
- Termara C Parker
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Michael J Crowley
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Adam J Naples
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Max J Rolison
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Jia Wu
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Julie A Trapani
- Department of Psychology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - James C McPartland
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
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14
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Levin AR, Naples AJ, Scheffler AW, Webb SJ, Shic F, Sugar CA, Murias M, Bernier RA, Chawarska K, Dawson G, Faja S, Jeste S, Nelson CA, McPartland JC, Şentürk D. Day-to-Day Test-Retest Reliability of EEG Profiles in Children With Autism Spectrum Disorder and Typical Development. Front Integr Neurosci 2020; 14:21. [PMID: 32425762 PMCID: PMC7204836 DOI: 10.3389/fnint.2020.00021] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Accepted: 03/23/2020] [Indexed: 01/11/2023] Open
Abstract
Biomarker development is currently a high priority in neurodevelopmental disorder research. For many types of biomarkers (particularly biomarkers of diagnosis), reliability over short periods is critically important. In the field of autism spectrum disorder (ASD), resting electroencephalography (EEG) power spectral densities (PSD) are well-studied for their potential as biomarkers. Classically, such data have been decomposed into pre-specified frequency bands (e.g., delta, theta, alpha, beta, and gamma). Recent technical advances, such as the Fitting Oscillations and One-Over-F (FOOOF) algorithm, allow for targeted characterization of the features that naturally emerge within an EEG PSD, permitting a more detailed characterization of the frequency band-agnostic shape of each individual's EEG PSD. Here, using two resting EEGs collected a median of 6 days apart from 22 children with ASD and 25 typically developing (TD) controls during the Feasibility Visit of the Autism Biomarkers Consortium for Clinical Trials, we estimate test-retest reliability based on the characterization of the PSD shape in two ways: (1) Using the FOOOF algorithm we estimate six parameters (offset, slope, number of peaks, and amplitude, center frequency and bandwidth of the largest alpha peak) that characterize the shape of the EEG PSD; and (2) using nonparametric functional data analyses, we decompose the shape of the EEG PSD into a reduced set of basis functions that characterize individual power spectrum shapes. We show that individuals exhibit idiosyncratic PSD signatures that are stable over recording sessions using both characterizations. Our data show that EEG activity from a brief 2-min recording provides an efficient window into characterizing brain activity at the single-subject level with desirable psychometric characteristics that persist across different analytical decomposition methods. This is a necessary step towards analytical validation of biomarkers based on the EEG PSD and provides insights into parameters of the PSD that offer short-term reliability (and thus promise as potential biomarkers of trait or diagnosis) vs. those that are more variable over the short term (and thus may index state or other rapidly dynamic measures of brain function). Future research should address the longer-term stability of the PSD, for purposes such as monitoring development or response to treatment.
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Affiliation(s)
- April R. Levin
- Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Adam J. Naples
- Child Study Center, School of Medicine, Yale University, New Haven, CT, United States
| | - Aaron Wolfe Scheffler
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States
| | - Sara J. Webb
- Center for Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States
| | - Frederick Shic
- Center for Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - Catherine A. Sugar
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Michael Murias
- Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL, United States
| | - Raphael A. Bernier
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States
| | - Katarzyna Chawarska
- Child Study Center, School of Medicine, Yale University, New Haven, CT, United States
| | - Geraldine Dawson
- Duke Institute for Brain Sciences, Duke University, Durham, NC, United States
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
| | - Susan Faja
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Shafali Jeste
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Charles A. Nelson
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - James C. McPartland
- Child Study Center, School of Medicine, Yale University, New Haven, CT, United States
| | - Damla Şentürk
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States
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15
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Duan S, Lee M, Wolf J, Naples AJ, McPartland JC. Higher Depressive Symptoms Predict Lower Social Adaptive Functioning in Children and Adolescents with ASD. J Clin Child Adolesc Psychol 2020; 51:203-210. [PMID: 32347746 DOI: 10.1080/15374416.2020.1750020] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Objective: Despite the frequent occurrence of depressive symptoms in children and adolescents with autism spectrum disorder (ASD), few studies have investigated the relationship between depressive symptoms and adaptive functioning. The present study explored the impact of depressive symptoms on different domains of adaptive functioning in children and adolescents with ASD.Methods: Depressive symptoms and adaptive functioning were analyzed in 62 children and adolescents with ASD (20 females) and 36 children and adolescents (15 females) with typical development between 5 and 18 years of age.Results: After controlling for IQ, age and sex, higher depressive symptoms predicted lower functioning in the social domain among children and adolescents with ASD. Depressive symptoms did not significantly predict communication or daily living skills.Conclusions: These findings highlight the relevance of depression in social adaptive function in ASD and emphasize the importance of assessing depressive symptomatology when evaluating social skills and planning treatment for children and adolescents with ASD.
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Affiliation(s)
- Suqian Duan
- Yale Child Study Center, School of Medicine, Yale University.,Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London
| | - Michelle Lee
- Yale Child Study Center, School of Medicine, Yale University.,Child Study Center, Department of Child and Adolescent Psychiatry, Hassenfeld Children's Hospital at NYU Langone
| | - Julie Wolf
- Yale Child Study Center, School of Medicine, Yale University
| | - Adam J Naples
- Yale Child Study Center, School of Medicine, Yale University
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16
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Rolison MJ, Naples AJ, Rutherford HJV, McPartland JC. The Presence of Another Person Influences Oscillatory Cortical Dynamics During Dual Brain EEG Recording. Front Psychiatry 2020; 11:246. [PMID: 32362842 PMCID: PMC7180176 DOI: 10.3389/fpsyt.2020.00246] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Accepted: 03/12/2020] [Indexed: 11/13/2022] Open
Abstract
Humans are innately social creatures and the social environment strongly influences brain development. As such, the human brain is primed for and sensitive to social information even in the absence of explicit task or instruction. In this study, we examined the influence of different levels of interpersonal proximity on resting state brain activity and its association with social cognition. We measured EEG in pairs of 13 typically developing (TD) adults seated in separate rooms, in the same room back-to-back, and in the same room facing each other. Interpersonal proximity modulated broadband EEG power from 4-55 Hz and individual differences in self-reported social cognition modulated these effects in the beta and gamma frequency bands. These findings provide novel insight into the influence of social environment on brain activity and its association with social cognition through dual-brain EEG recording and demonstrate the importance of using interactive methods to study the human brain.
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17
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McPartland JC, Bernier RA, Jeste SS, Dawson G, Nelson CA, Chawarska K, Earl R, Faja S, Johnson SP, Sikich L, Brandt CA, Dziura JD, Rozenblit L, Hellemann G, Levin AR, Murias M, Naples AJ, Platt ML, Sabatos-DeVito M, Shic F, Senturk D, Sugar CA, Webb SJ. The Autism Biomarkers Consortium for Clinical Trials (ABC-CT): Scientific Context, Study Design, and Progress Toward Biomarker Qualification. Front Integr Neurosci 2020; 14:16. [PMID: 32346363 PMCID: PMC7173348 DOI: 10.3389/fnint.2020.00016] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 03/10/2020] [Indexed: 12/19/2022] Open
Abstract
Clinical research in neurodevelopmental disorders remains reliant upon clinician and caregiver measures. Limitations of these approaches indicate a need for objective, quantitative, and reliable biomarkers to advance clinical research. Extant research suggests the potential utility of multiple candidate biomarkers; however, effective application of these markers in trials requires additional understanding of replicability, individual differences, and intra-individual stability over time. The Autism Biomarkers Consortium for Clinical Trials (ABC-CT) is a multi-site study designed to investigate a battery of electrophysiological (EEG) and eye-tracking (ET) indices as candidate biomarkers for autism spectrum disorder (ASD). The study complements published biomarker research through: inclusion of large, deeply phenotyped cohorts of children with ASD and typical development; a longitudinal design; a focus on well-evidenced candidate biomarkers harmonized with an independent sample; high levels of clinical, regulatory, technical, and statistical rigor; adoption of a governance structure incorporating diverse expertise in the ASD biomarker discovery and qualification process; prioritization of open science, including creation of a repository containing biomarker, clinical, and genetic data; and use of economical and scalable technologies that are applicable in developmental populations and those with special needs. The ABC-CT approach has yielded encouraging results, with one measure accepted into the FDA’s Biomarker Qualification Program to date. Through these advances, the ABC-CT and other biomarker studies in progress hold promise to deliver novel tools to improve clinical trials research in ASD.
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Affiliation(s)
| | - Raphael A Bernier
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle Children's Hospital, Seattle, WA, United States.,Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
| | - Shafali S Jeste
- University of California, Los Angeles, Los Angeles, CA, United States
| | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | - Charles A Nelson
- Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Harvard University, Boston, MA, United States
| | | | - Rachel Earl
- Center on Human Development and Disability, University of Washington, Seattle, WA, United States
| | - Susan Faja
- Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Harvard University, Boston, MA, United States
| | - Scott P Johnson
- University of California, Los Angeles, Los Angeles, CA, United States
| | - Linmarie Sikich
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | | | | | | | - Gerhard Hellemann
- University of California, Los Angeles, Los Angeles, CA, United States
| | - April R Levin
- Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Harvard University, Boston, MA, United States
| | | | - Adam J Naples
- Yale Child Study Center, New Haven, CT, United States
| | | | - Maura Sabatos-DeVito
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | - Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle Children's Hospital, Seattle, WA, United States.,Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, United States
| | - Damla Senturk
- University of California, Los Angeles, Los Angeles, CA, United States
| | - Catherine A Sugar
- University of California, Los Angeles, Los Angeles, CA, United States
| | - Sara J Webb
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle Children's Hospital, Seattle, WA, United States.,Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
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Webb SJ, Shic F, Murias M, Sugar CA, Naples AJ, Barney E, Borland H, Hellemann G, Johnson S, Kim M, Levin AR, Sabatos-DeVito M, Santhosh M, Senturk D, Dziura J, Bernier RA, Chawarska K, Dawson G, Faja S, Jeste S, McPartland J. Biomarker Acquisition and Quality Control for Multi-Site Studies: The Autism Biomarkers Consortium for Clinical Trials. Front Integr Neurosci 2020; 13:71. [PMID: 32116579 PMCID: PMC7020808 DOI: 10.3389/fnint.2019.00071] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Accepted: 11/28/2019] [Indexed: 12/31/2022] Open
Abstract
The objective of the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) is to evaluate a set of lab-based behavioral video tracking (VT), electroencephalography (EEG), and eye tracking (ET) measures for use in clinical trials with children with autism spectrum disorder (ASD). Within the larger organizational structure of the ABC-CT, the Data Acquisition and Analytic Core (DAAC) oversees the standardization of VT, EEG, and ET data acquisition, data processing, and data analysis. This includes designing and documenting data acquisition and analytic protocols and manuals; facilitating site training in acquisition; data acquisition quality control (QC); derivation and validation of dependent variables (DVs); and analytic deliverables including preparation of data for submission to the National Database for Autism Research (NDAR). To oversee consistent application of scientific standards and methodological rigor for data acquisition, processing, and analytics, we developed standard operating procedures that reflect the logistical needs of multi-site research, and the need for well-articulated, transparent processes that can be implemented in future clinical trials. This report details the methodology of the ABC-CT related to acquisition and QC in our Feasibility and Main Study phases. Based on our acquisition metrics from a preplanned interim analysis, we report high levels of acquisition success utilizing VT, EEG, and ET experiments in a relatively large sample of children with ASD and typical development (TD), with data acquired across multiple sites and use of a manualized training and acquisition protocol.
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Affiliation(s)
- Sara Jane Webb
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
| | - Frederick Shic
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
- Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, United States
| | - Michael Murias
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | - Catherine A. Sugar
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Statistics, University of California, Los Angeles, Los Angeles, CA, United States
| | - Adam J. Naples
- Yale Child Study Center, Yale University, New Haven, CT, United States
| | - Erin Barney
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - Heather Borland
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - Gerhard Hellemann
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Scott Johnson
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Minah Kim
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - April R. Levin
- Department of Neurology, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Harvard University, Boston, MA, United States
| | - Maura Sabatos-DeVito
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | - Megha Santhosh
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - Damla Senturk
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Statistics, University of California, Los Angeles, Los Angeles, CA, United States
| | - James Dziura
- Yale Child Study Center, Yale University, New Haven, CT, United States
| | - Raphael A. Bernier
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
- Center on Human Development and Disability, University of Washington, Seattle, WA, United States
| | | | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | - Susan Faja
- Harvard Medical School, Harvard University, Boston, MA, United States
- Department of Pediatrics, Boston Children’s Hospital, Boston, MA, United States
| | - Shafali Jeste
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Neurology, University of California, Los Angeles, Los Angeles, CA, United States
| | - James McPartland
- Yale Child Study Center, Yale University, New Haven, CT, United States
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Abstract
In adults with autism spectrum disorder, co-occurring psychiatric conditions are prevalent, and depression is one of the most common co-occurring disorders. This study examined the relationship between depression and cognitive ability, autism symptom severity, and self-reported social impairments in autism spectrum disorder. A total of 33 adults with autism spectrum disorder and 28 adults with typical development completed a standardized psychiatric interview, cognitive test, measure of clinician-rated autism symptom severity, and self-report of social impairments. Nine participants with autism spectrum disorder (27%) met the criteria for a depressive disorder (autism spectrum disorder + depressive disorder). Relatively more females with autism spectrum disorder had a co-occurring depressive disorder. The typical development group had a higher intelligence quotient than the autism spectrum disorder group, but the autism spectrum disorder + depressive disorder group did not differ from the typical development or autism spectrum disorder group. While the autism spectrum disorder + depressive disorder group had lower clinician-rated autism symptom severity than the autism spectrum disorder group, the autism spectrum disorder + depressive disorder group reported more social impairments than the autism spectrum disorder group. Self-reported social impairments predicted depression in adults with autism spectrum disorder when accounting for symptom severity and cognitive ability. These findings suggest that more self-perceived social impairments are related to depressive disorders in autism spectrum disorder, and may help clinicians identify individuals who are vulnerable in developing a co-occurring depressive disorder. Future directions include follow-up studies with larger cohorts and longitudinal designs to support inferences regarding directionality of these relationships.
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Trevisan DA, Foss-Feig JH, Naples AJ, Srihari V, Anticevic A, McPartland JC. Autism Spectrum Disorder and Schizophrenia Are Better Differentiated by Positive Symptoms Than Negative Symptoms. Front Psychiatry 2020; 11:548. [PMID: 32595540 PMCID: PMC7301837 DOI: 10.3389/fpsyt.2020.00548] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2020] [Accepted: 05/28/2020] [Indexed: 01/01/2023] Open
Abstract
Autism spectrum disorder (ASD) and schizophrenia (SZ) are heterogenous neurodevelopmental disorders that overlap in symptom presentation. The purpose of this study was to specify overlapping symptom domains and to identify symptoms that can reliably differentiate adults with ASD (n = 53), SZ (n = 39), and typical development (TD; n = 40). All participants regardless of diagnosis were administered gold-standard diagnostic assessments of ASD and SZ characteristics including the Autism Diagnostic Observation Schedule (ADOS-2) and the Positive and Negative Syndrome Scale (PANSS). Sensitivity and specificity of the ADOS were assessed using diagnostic cut-off scores. The degree of symptom overlap on these measures between participant groups was analyzed using Analyses of Variance (ANOVAs), Receiver Operating Characteristic (ROC) Curves, and Analyses of Covariance (ANCOVAs) to control for group differences in IQ and sex distributions. The ADOS reliably discriminated ASD and TD adults, but there was a high rate of "false positives" in SZ patients who did not meet the DSM-5 criteria for ASD. To identify the reasons for low specificity in the SZ sample, we categorized ASD and SZ symptoms into 'positive' (presence of atypical behaviors) and 'negative' (absence of typical behaviors) symptoms. ASD and SZ groups overlapped on negative symptoms largely related to the absence of typical social and communicative behaviors, whereas disorder-specific positive symptoms differentiated ASD and SZ. For example, those with ASD scored higher on restricted and repetitive behaviors and stereotyped language, whereas those with SZ scored higher on psychotic symptoms such as delusions and hallucinations. These results suggest that, when making a differential diagnosis between ASD and SZ, clinicians may benefit from focusing on the presence or absence of positive ASD and SZ symptoms. Standardized measures to classify ASD symptoms into positive and negative symptoms have not yet been developed but represent a potentially viable clinical tool.
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Affiliation(s)
- Dominic A Trevisan
- Child Study Center, Yale University School of Medicine, New Haven, CT, United States
| | - Jennifer H Foss-Feig
- Department of Psychiatry, Mount Sinai Icahn School of Medicine, New York, NY, United States.,Seaver Autism Center for Research and Treatment Mount Sinai Icahn School of Medicine, New York, NY, United States
| | - Adam J Naples
- Child Study Center, Yale University School of Medicine, New Haven, CT, United States
| | - Vinod Srihari
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Alan Anticevic
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - James C McPartland
- Child Study Center, Yale University School of Medicine, New Haven, CT, United States
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21
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Desai A, Foss-Feig JH, Naples AJ, Coffman M, Trevisan DA, McPartland JC. Autistic and alexithymic traits modulate distinct aspects of face perception. Brain Cogn 2019; 137:103616. [PMID: 31734588 DOI: 10.1016/j.bandc.2019.103616] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 09/16/2019] [Accepted: 09/19/2019] [Indexed: 10/25/2022]
Abstract
BACKGROUND Atypical face processing is a prominent feature of autism spectrum disorder (ASD) but is not universal and is subject to individual variability. This heterogeneity could be accounted for by reliable yet unidentified subgroups within the diverse population of individuals with ASD. Alexithymia, which is characterized by difficulties in emotion recognition and identification, serves as a potential grouping factor. Recent research demonstrates that emotion recognition impairments in ASD are predicted by its comorbidity with alexithymia. The current study assessed the relative influence of autistic versus alexithymic traits on neural indices of face and emotion perception. METHODS Capitalizing upon the temporal sensitivity of event-related potentials (ERPs), it investigates the distinct contributions of alexithymic versus autistic traits at specific stages of emotional face processing in 27 typically developing adults (18 female). ERP components reflecting sequential stages of perceptual processing (P100, N170 and N250) were recorded in response to fear and neutral faces. RESULTS The results indicated that autistic traits were associated with structural encoding of faces (N170), whereas alexithymic traits were associated with more complex emotion decoding (N250). CONCLUSIONS These findings have important implications for deconstructing heterogeneity within ASD.
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Affiliation(s)
- Aishani Desai
- Yale Child Study Center, Yale University, New Haven, CT 06519, United States; Department of Psychology, Macquarie University, Sydney, Australia
| | - Jennifer H Foss-Feig
- Yale Child Study Center, Yale University, New Haven, CT 06519, United States; Department of Psychiatry and Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Adam J Naples
- Yale Child Study Center, Yale University, New Haven, CT 06519, United States
| | - Marika Coffman
- Yale Child Study Center, Yale University, New Haven, CT 06519, United States; Department of Psychology, Virginia Polytechnic Institute and State University, Blacksburg, VA 24060, United States
| | - Dominic A Trevisan
- Yale Child Study Center, Yale University, New Haven, CT 06519, United States
| | - James C McPartland
- Yale Child Study Center, Yale University, New Haven, CT 06519, United States.
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Cole EJ, Enticott PG, Oberman LM, Gwynette MF, Casanova MF, Jackson SLJ, Jannati A, McPartland JC, Naples AJ, Puts NAJ. The Potential of Repetitive Transcranial Magnetic Stimulation for Autism Spectrum Disorder: A Consensus Statement. Biol Psychiatry 2019; 85:e21-e22. [PMID: 30103951 PMCID: PMC6342639 DOI: 10.1016/j.biopsych.2018.06.003] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 06/07/2018] [Indexed: 11/15/2022]
Affiliation(s)
- Eleanor J Cole
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, California.
| | - Peter G Enticott
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Victoria, Australia
| | - Lindsay M Oberman
- Neuroplasticity and Autism Spectrum Disorder Program and Department of Psychiatry and Human Behavior, E.P. Bradley Hospital and Warren Alpert Medical School, Brown University, Providence, Rhode Island
| | - M Frampton Gwynette
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina
| | - Manuel F Casanova
- Department of Psychiatry and Behavioral Sciences, University of Louisville, Louisville, Kentucky
| | - Scott L J Jackson
- Child Study Center, Yale School of Medicine, Yale University, New Haven, Connecticut
| | - Ali Jannati
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - James C McPartland
- Child Study Center, Yale School of Medicine, Yale University, New Haven, Connecticut
| | - Adam J Naples
- Child Study Center, Yale School of Medicine, Yale University, New Haven, Connecticut
| | - Nicolaas A J Puts
- Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medicine, Baltimore, Maryland
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23
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Carter Leno V, Tomlinson SB, Chang SAA, Naples AJ, McPartland JC. Resting-state alpha power is selectively associated with autistic traits reflecting behavioral rigidity. Sci Rep 2018; 8:11982. [PMID: 30097597 PMCID: PMC6086866 DOI: 10.1038/s41598-018-30445-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Accepted: 07/29/2018] [Indexed: 11/12/2022] Open
Abstract
Previous research suggests that variation in at-rest neural activity correlates with specific domains of the ASD phenotype; however, few studies have linked patterns of brain activity with autistic trait expression in typically developing populations. The purpose of this study was to examine associations between resting-state electroencephalography (EEG) and three domains of the broader autism phenotype (social interest, rigidity, and pragmatic language) in typically developing individuals. High-density scalp EEG was recorded in thirty-seven typically developing adult participants (13 male, aged 18-52 years). The Broad Autism Phenotype Questionnaire (BAP-Q) was used to measure autistic trait expression. Absolute alpha power (8-13 Hz) was extracted from eyes-closed epochs using spectral decomposition techniques. Analyses revealed a specific positive association between scores on the BAP-Q Rigidity subscale and alpha power in the parietal scalp region. No significant associations were found between alpha power and the BAP-Q Aloofness or Pragmatic Language subscales. Furthermore, the association between EEG power and behavioral rigidity was specific to the alpha frequency band. This study demonstrates that specific traits within the broader autism phenotype are associated with dissociable patterns of at-rest neural activity.
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Affiliation(s)
- Virginia Carter Leno
- Yale Child Study Center, 230 South Frontage Road, New Haven, 06520, CT, USA
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK
| | - Samuel B Tomlinson
- Yale Child Study Center, 230 South Frontage Road, New Haven, 06520, CT, USA
- School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, 14642, NY, USA
| | - Shou-An A Chang
- Yale Child Study Center, 230 South Frontage Road, New Haven, 06520, CT, USA
| | - Adam J Naples
- Yale Child Study Center, 230 South Frontage Road, New Haven, 06520, CT, USA
| | - James C McPartland
- Yale Child Study Center, 230 South Frontage Road, New Haven, 06520, CT, USA.
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24
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Rolison MJ, Naples AJ, Rutherford HJV, McPartland JC. Modulation of reward in a live social context as revealed through interactive social neuroscience. Soc Neurosci 2018; 13:416-428. [PMID: 28586261 PMCID: PMC6072262 DOI: 10.1080/17470919.2017.1339635] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Revised: 05/09/2017] [Indexed: 01/09/2023]
Abstract
Social neuroscience research investigating autism spectrum disorder (ASD) has yielded inconsistent findings, despite ASD being well-characterized by difficulties in social interaction and communication through behavioral observation. In particular, specific etiologies and functional and structural assays of the brain in autism have not been consistently identified. To date, most social neuroscience research has focused on a single person viewing static images. Research utilizing interactive social neuroscience featuring dual-brain recording offers great promise for the study of neurodevelopmental disabilities. Reward processing has been implicated in the pathology of ASD, yet mixed findings have brought uncertainty about the role reward processing deficits may play in ASD. The current study employed dual-brain EEG recording to examine reward processing during live interaction and its relation to autistic traits. Sixteen typically developing (TD) adults played a competitive treasure-hunt game against a computer and against a human partner. EEG results revealed enhanced neural sensitivity to reward outcome during live interaction with a human competitor. Further, individuals with higher levels of autistic traits demonstrated reduced sensitivity to reward outcome during live interaction. These findings provide novel insight into reward processing mechanisms associated with autistic traits, as well as support the necessary utility of interactive social neuroscience techniques to study developmental disorders.
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Affiliation(s)
- Max J Rolison
- a Child Study Center , Yale School of Medicine , New Haven , CT , USA
| | - Adam J Naples
- a Child Study Center , Yale School of Medicine , New Haven , CT , USA
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Naples AJ, Wu J, Mayes LC, McPartland JC. Event-related potentials index neural response to eye contact. Biol Psychol 2017; 127:18-24. [PMID: 28396215 DOI: 10.1016/j.biopsycho.2017.04.006] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2016] [Revised: 02/22/2017] [Accepted: 04/05/2017] [Indexed: 10/19/2022]
Abstract
Sensitivity to eye-contact is a foundation upon which social cognition is built. However, there are no known neural markers characterizing response to reciprocal gaze. Using co-registered EEG and eye-tracking, we measured brain activity while participants viewed faces that responded to their looking patterns. Contingent upon participant gaze, onscreen faces opened their eyes or mouths; in this way we measured brain response to reciprocal eye-contact. We identified two ERP components that were largest in response to reciprocal eye-contact: the N170 and the P300. The magnitude of the components' differences between reciprocal eye-contact and mouth movement predicted self-reported social function. Individuals with greater brain response to reciprocal eye-contact reported more normative scores on measures of autistic traits. These results present the first neural markers of eye-contact, revealing that reciprocal eye-contact is identified in less than 500ms. Furthermore, individual differences in brain response to eye-contact predict meaningful variability in self-reports of social performance.
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Affiliation(s)
- Adam J Naples
- Yale University School of Medicine, Child Study Center, 230 South Frontage Road, New Haven, CT, 06520, United States.
| | - Jia Wu
- Yale University School of Medicine, Child Study Center, 230 South Frontage Road, New Haven, CT, 06520, United States.
| | - Linda C Mayes
- Yale University School of Medicine, Child Study Center, 230 South Frontage Road, New Haven, CT, 06520, United States.
| | - James C McPartland
- Yale University School of Medicine, Child Study Center, 230 South Frontage Road, New Haven, CT, 06520, United States.
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26
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Cox A, Kohls G, Naples AJ, Mukerji CE, Coffman MC, Rutherford HJV, Mayes LC, McPartland JC. Diminished social reward anticipation in the broad autism phenotype as revealed by event-related brain potentials. Soc Cogn Affect Neurosci 2015; 10:1357-64. [PMID: 25752905 PMCID: PMC4590535 DOI: 10.1093/scan/nsv024] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2014] [Revised: 01/22/2015] [Accepted: 03/04/2015] [Indexed: 01/10/2023] Open
Abstract
Diminished responsivity to reward incentives is a key contributor to the social-communication problems seen in autism spectrum disorders (ASDs). Social motivation theories suggest that individuals with ASD do not experience social interactions as rewarding, leading to negative consequences for the development of brain circuitry subserving social information. In this study, we examined neural responses to social and non-social reward anticipation in 35 typically developing young adults, examining modulation of reward sensitivity by level of autistic traits. Using an Event-related potential incentive-delay task incorporating novel, more ecologically valid forms of reward, higher expression of autistic traits was associated with an attenuated P3 response to the anticipation of social (simulated real-time video feedback from an observer), but not non-social (candy), rewards. Exploratory analyses revealed that this was unrelated to mentalizing ability. The P3 component reflects motivated attention to reward signals, suggesting attenuated motivation allocation specific to social incentives. The study extends prior findings of atypical reward anticipation in ASD, demonstrating that attenuated social reward responsiveness extends to autistic traits in the range of typical functioning. Results support the development of innovative paradigms for investigating social and non-social reward responsiveness. Insight into vulnerabilities in reward processing is critical for understanding social function in ASD.
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Affiliation(s)
- Anthony Cox
- Yale Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Gregor Kohls
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Medical Faculty, RWTH Aachen University Hospital, Aachen, Germany
| | - Adam J Naples
- Yale Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Cora E Mukerji
- Department of Psychology, Harvard University, Cambridge, MA, USA, and
| | - Marika C Coffman
- Department of Psychology, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
| | | | - Linda C Mayes
- Yale Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - James C McPartland
- Yale Child Study Center, Yale University School of Medicine, New Haven, CT, USA
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27
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Rolison MJ, Naples AJ, McPartland JC. Interactive social neuroscience to study autism spectrum disorder. Yale J Biol Med 2015; 88:17-24. [PMID: 25745371 PMCID: PMC4345534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Individuals with autism spectrum disorder (ASD) demonstrate difficulty with social interactions and relationships, but the neural mechanisms underlying these difficulties remain largely unknown. While social difficulties in ASD are most apparent in the context of interactions with other people, most neuroscience research investigating ASD have provided limited insight into the complex dynamics of these interactions. The development of novel, innovative "interactive social neuroscience" methods to study the brain in contexts with two interacting humans is a necessary advance for ASD research. Studies applying an interactive neuroscience approach to study two brains engaging with one another have revealed significant differences in neural processes during interaction compared to observation in brain regions that are implicated in the neuropathology of ASD. Interactive social neuroscience methods are crucial in clarifying the mechanisms underlying the social and communication deficits that characterize ASD.
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Affiliation(s)
| | | | - James C. McPartland
- Yale Child Study Center, New Haven, Connecticut,James C. McPartland, PhD, Yale Child Study Center, 230 South Frontage Road, New Haven, CT 06520; Tele: 203-785-7179; Fax: 203-737-4197;
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28
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McPartland JC, Crowley MJ, Perszyk DR, Mukerji CE, Naples AJ, Wu J, Mayes LC. Preserved reward outcome processing in ASD as revealed by event-related potentials. J Neurodev Disord 2012; 4:16. [PMID: 22958616 PMCID: PMC3436639 DOI: 10.1186/1866-1955-4-16] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2012] [Accepted: 05/31/2012] [Indexed: 12/16/2022] Open
Abstract
Background Problems with reward system function have been posited as a primary difficulty in autism spectrum disorders. The current study examined an electrophysiological marker of feedback monitoring, the feedback-related negativity (FRN), during a monetary reward task. The study advanced prior understanding by focusing exclusively on a developmental sample, applying rigorous diagnostic characterization and introducing an experimental paradigm providing more subtly different feedback valence (reward versus non-reward instead of reward versus loss). Methods Twenty-six children with autism spectrum disorder and 28 typically developing peers matched on age and full-scale IQ played a guessing game resulting in monetary gain (“win”) or neutral outcome (“draw”). ERP components marking early visual processing (N1, P2) and feedback appraisal (FRN) were contrasted between groups in each condition, and their relationships to behavioral measures of social function and dysfunction, social anxiety, and autism symptomatology were explored. Results FRN was observed on draw trials relative to win trials. Consistent with prior research, children with ASD exhibited a FRN to suboptimal outcomes that was comparable to typical peers. ERP parameters were unrelated to behavioral measures. Conclusions Results of the current study indicate typical patterns of feedback monitoring in the context of monetary reward in ASD. The study extends prior findings of normative feedback monitoring to a sample composed exclusively of children and demonstrates that, as in typical development, individuals with autism exhibit a FRN to suboptimal outcomes, irrespective of neutral or negative valence. Results do not support a pervasive problem with reward system function in ASD, instead suggesting any dysfunction lies in more specific domains, such as social perception, or in response to particular feedback-monitoring contexts, such as self-evaluation of one’s errors.
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Affiliation(s)
- James C McPartland
- Yale Child Study Center, Yale University School of Medicine, 230 South Frontage Road, New Haven, CT, USA.
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29
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Naples AJ, Chang JT, Katz L, Grigorenko EL. Same or different? Insights into the etiology of phonological awareness and rapid naming. Biol Psychol 2009; 80:226-39. [PMID: 19007845 PMCID: PMC2708917 DOI: 10.1016/j.biopsycho.2008.10.002] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2008] [Revised: 10/11/2008] [Accepted: 10/13/2008] [Indexed: 01/28/2023]
Abstract
This work's objective was to offer additional insights into the psychological and genetic bases of reading ability and disability, and to evaluate the plausibility of a variety of psychological models of reading involving phonological awareness (PA) and rapid naming (RN), both hypothesized to be principal components in such models. In Study 1, 488 unselected families were assessed with measures of PA and RN to investigate familial aggregation and to obtain estimates of both the number and effect-magnitude of genetic loci involved in these traits' transmission. The results of the analyses from Study 1 indicated the presence of genetic effects in the etiology of individual differences for PA and RN and pointed to both the shared and unique sources of this genetic variance, which appeared to be exerted by multiple (3-6 for PA and 3-5 for RN) genes. These results were used in Study 2 to parameterize a simulation of 3000 families with quantitatively distributed PA and RN, so that the robustness and generalizability of the Study 1 findings could be evaluated. The findings of both studies were interpreted according to established theories of reading and our own understanding of the etiology of complex developmental disorders.
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Affiliation(s)
| | | | - Leonard Katz
- Department of Psychology, University of Connecticut, USA
- Haskins Laboratories, Yale University, USA
| | - Elena L. Grigorenko
- Department of Psychology, Yale University, USA
- Child Study Center and Department of Epidemiology and Public Health, Yale University, School of Medicine, USA
- Department of Psychology, Moscow State University, Russia
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Abstract
We compared the reading-related skills of children with Autism Spectrum Disorders who have hyperlexia (ASD + HPL) with age-matched children with ASD without HPL (ASD - HPL) and with single-word reading-matched typically developing children (TYP). Children with ASD + HPL performed (1) better than did children with ASD - HPL on tasks of single-word reading and pseudoword decoding and (2) equivalently well compared to word-reading-matched TYP children on all reading-related tasks except reading comprehension. It appears that the general underlying model of single-word reading is the same in principle for "typical" and hyperlexic reading. Yet, the study revealed some dissimilarities between these two types of reading when more fine-grained cognitive and linguistic abilities were considered; these dissimilarities warrant further investigations.
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