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Dickinson A, Booth M, Daniel M, Campbell A, Miller N, Lau B, Zempel J, Webb SJ, Elison J, Lee AKC, Estes A, Dager S, Hazlett H, Wolff J, Schultz R, Marrus N, Evans A, Piven J, Pruett JR, Jeste S. Multi-site EEG studies in early infancy: Methods to enhance data quality. Dev Cogn Neurosci 2024; 69:101425. [PMID: 39163782 PMCID: PMC11380169 DOI: 10.1016/j.dcn.2024.101425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 07/30/2024] [Accepted: 07/30/2024] [Indexed: 08/22/2024] Open
Abstract
Brain differences linked to autism spectrum disorder (ASD) can manifest before observable symptoms. Studying these early neural precursors in larger and more diverse cohorts is crucial for advancing our understanding of developmental pathways and potentially facilitating earlier identification. EEG is an ideal tool for investigating early neural differences in ASD, given its scalability and high tolerability in infant populations. In this context, we integrated EEG into an existing multi-site MRI study of infants with a higher familial likelihood of developing ASD. This paper describes the comprehensive protocol established to collect longitudinal, high-density EEG data from infants across five sites as part of the Infant Brain Imaging Study (IBIS) Network and reports interim feasibility and data quality results. We evaluated feasibility by measuring the percentage of infants from whom we successfully collected each EEG paradigm. The quality of task-free data was assessed based on the duration of EEG recordings remaining after artifact removal. Preliminary analyses revealed low data loss, with average in-session loss rates at 4.16 % and quality control loss rates at 11.66 %. Overall, the task-free data retention rate, accounting for both in-session issues and quality control, was 84.16 %, with high consistency across sites. The insights gained from this preliminary analysis highlight key sources of data attrition and provide practical considerations to guide similar research endeavors.
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Affiliation(s)
- Abigail Dickinson
- Center for Autism Research and Treatment, Semel Institute for Neuroscience, University of California, Los Angeles, CA, USA.
| | - Madison Booth
- Department of Neurology, Children's Hospital of Los Angeles, Los Angeles, CA, USA
| | - Manjari Daniel
- Center for Autism Research and Treatment, Semel Institute for Neuroscience, University of California, Los Angeles, CA, USA
| | - Alana Campbell
- Carolina Institute for Developmental Disabilities, Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Neely Miller
- Center for Neurobehavioral Development, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Bonnie Lau
- Department of Otolaryngology - Head and Neck Surgery, University of Washington, Seattle, WA, USA
| | - John Zempel
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Sara Jane Webb
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, Seattle, WA, USA
| | - Jed Elison
- Institute of Child Development, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Adrian K C Lee
- Department of Speech and Hearing Sciences, Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, USA
| | - Annette Estes
- Department of Speech and Hearing Sciences, Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, USA
| | - Stephen Dager
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Heather Hazlett
- Carolina Institute for Developmental Disabilities, Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jason Wolff
- Center for Neurobehavioral Development, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Robert Schultz
- Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Natasha Marrus
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Alan Evans
- McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Joseph Piven
- Carolina Institute for Developmental Disabilities, Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - John R Pruett
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Shafali Jeste
- Department of Neurology, Children's Hospital of Los Angeles, Los Angeles, CA, USA; Department of Pediatrics and Neurology, University of Southern California, Los Angeles, CA, USA
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2
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Barnes SJK, Bjerkan J, Clemson PT, Newman J, Stefanovska A. Phase coherence-A time-localized approach to studying interactions. CHAOS (WOODBURY, N.Y.) 2024; 34:073155. [PMID: 39052926 DOI: 10.1063/5.0202865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 06/13/2024] [Indexed: 07/27/2024]
Abstract
Coherence measures the similarity of progression of phases between oscillations or waves. When applied to multi-scale, nonstationary dynamics with time-varying amplitudes and frequencies, high values of coherence provide a useful indication of interactions, which might otherwise go unnoticed. However, the choice of analyzing coherence based on phases and amplitudes (amplitude-weighted phase coherence) vs only phases (phase coherence) has long been seen as arbitrary. Here, we review the concept of coherence and focus on time-localized methods of analysis, considering both phase coherence and amplitude-weighted phase coherence. We discuss the importance of using time-localized analysis and illustrate the methods and their practicalities on both numerically modeled and real time-series. The results show that phase coherence is more robust than amplitude-weighted phase coherence to both noise perturbations and movement artifacts. The results also have wider implications for the analysis of real data and the interpretation of physical systems.
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Affiliation(s)
- S J K Barnes
- Physics Department, Lancaster University, Lancaster LA1 4YB, United Kingdom
| | - J Bjerkan
- Physics Department, Lancaster University, Lancaster LA1 4YB, United Kingdom
| | - P T Clemson
- Physics Department, Lancaster University, Lancaster LA1 4YB, United Kingdom
| | - J Newman
- Department of Mathematics and Statistics, University of Exeter, Exeter, United Kingdom
| | - A Stefanovska
- Physics Department, Lancaster University, Lancaster LA1 4YB, United Kingdom
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3
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Cohenour T, Dickinson A, Jeste S, Gulsrud A, Kasari C. Patterns of spontaneous neural activity associated with social communication abilities among infants and toddlers showing signs of autism. Eur J Neurosci 2024; 60:3597-3613. [PMID: 38703054 DOI: 10.1111/ejn.16358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 03/28/2024] [Accepted: 04/02/2024] [Indexed: 05/06/2024]
Abstract
Early disruptions to social communication development, including delays in joint attention and language, are among the earliest markers of autism spectrum disorder (autism, henceforth). Although social communication differences are a core feature of autism, there is marked heterogeneity in social communication-related development among infants and toddlers exhibiting autism symptoms. Neural markers of individual differences in joint attention and language abilities may provide important insight into heterogeneity in autism symptom expression during infancy and toddlerhood. This study examined patterns of spontaneous electroencephalography (EEG) activity associated with joint attention and language skills in 70 community-referred 12- to 23-month-olds with autism symptoms and elevated scores on an autism diagnostic instrument. Data-driven cluster-based permutation analyses revealed significant positive associations between relative alpha power (6-9 Hz) and concurrent response to joint attention skills, receptive language, and expressive language abilities. Exploratory analyses also revealed significant negative associations between relative alpha power and measures of core autism features (i.e., social communication difficulties and restricted/repetitive behaviors). These findings shed light on the neural mechanisms underlying typical and atypical social communication development in emerging autism and provide a foundation for future work examining neural predictors of social communication growth and markers of intervention response.
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Affiliation(s)
- Torrey Cohenour
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, California, USA
| | - Abigail Dickinson
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, California, USA
| | - Shafali Jeste
- Division of Neurology, Children's Hospital Los Angeles, Los Angeles, California, USA
| | - Amanda Gulsrud
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, California, USA
| | - Connie Kasari
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, California, USA
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4
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Nelson CA, Sullivan E, Engelstad AM. Annual Research Review: Early intervention viewed through the lens of developmental neuroscience. J Child Psychol Psychiatry 2024; 65:435-455. [PMID: 37438865 DOI: 10.1111/jcpp.13858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/24/2023] [Indexed: 07/14/2023]
Abstract
The overarching goal of this paper is to examine the efficacy of early intervention when viewed through the lens of developmental neuroscience. We begin by briefly summarizing neural development from conception through the first few postnatal years. We emphasize the role of experience during the postnatal period, and consistent with decades of research on critical periods, we argue that experience can represent both a period of opportunity and a period of vulnerability. Because plasticity is at the heart of early intervention, we next turn our attention to the efficacy of early intervention drawing from two distinct literatures: early intervention services for children growing up in disadvantaged environments, and children at elevated likelihood of developing a neurodevelopmental delay or disorder. In the case of the former, we single out interventions that target caregiving and in the case of the latter, we highlight recent work on autism. A consistent theme throughout our review is a discussion of how early intervention is embedded in the developing brain. We conclude our article by discussing the implications our review has for policy, and we then offer recommendations for future research.
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Affiliation(s)
- Charles A Nelson
- Department of Pediatrics and Neuroscience, Harvard Medical School, Boston, MA, USA
- Division of Developmental Medicine, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
- Harvard Graduate School of Education, Cambridge, MA, USA
| | - Eileen Sullivan
- Division of Developmental Medicine, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
- Harvard Graduate School of Education, Cambridge, MA, USA
| | - Anne-Michelle Engelstad
- Division of Developmental Medicine, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
- Harvard Graduate School of Education, Cambridge, MA, USA
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5
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Sun B, Wang B, Wei Z, Feng Z, Wu ZL, Yassin W, Stone WS, Lin Y, Kong XJ. Identification of diagnostic markers for ASD: a restrictive interest analysis based on EEG combined with eye tracking. Front Neurosci 2023; 17:1236637. [PMID: 37886678 PMCID: PMC10598595 DOI: 10.3389/fnins.2023.1236637] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 09/12/2023] [Indexed: 10/28/2023] Open
Abstract
Electroencephalography (EEG) functional connectivity (EFC) and eye tracking (ET) have been explored as objective screening methods for autism spectrum disorder (ASD), but no study has yet evaluated restricted and repetitive behavior (RRBs) simultaneously to infer early ASD diagnosis. Typically developing (TD) children (n = 27) and ASD (n = 32), age- and sex-matched, were evaluated with EFC and ET simultaneously, using the restricted interest stimulus paradigm. Network-based machine learning prediction (NBS-predict) was used to identify ASD. Correlations between EFC, ET, and Autism Diagnostic Observation Schedule-Second Edition (ADOS-2) were performed. The Area Under the Curve (AUC) of receiver-operating characteristics (ROC) was measured to evaluate the predictive performance. Under high restrictive interest stimuli (HRIS), ASD children have significantly higher α band connectivity and significantly more total fixation time (TFT)/pupil enlargement of ET relative to TD children (p = 0.04299). These biomarkers were not only significantly positively correlated with each other (R = 0.716, p = 8.26e-4), but also with ADOS total scores (R = 0.749, p = 34e-4) and RRBs sub-score (R = 0.770, p = 1.87e-4) for EFC (R = 0.641, p = 0.0148) for TFT. The accuracy of NBS-predict in identifying ASD was 63.4%. ROC curve demonstrated TFT with 91 and 90% sensitivity, and 78.7% and 77.4% specificity for ADOS total and RRB sub-scores, respectively. Simultaneous EFC and ET evaluation in ASD is highly correlated with RRB symptoms measured by ADOS-2. NBS-predict of EFC offered a direct prediction of ASD. The use of both EFC and ET improve early ASD diagnosis.
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Affiliation(s)
- Binbin Sun
- Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Bryan Wang
- Martinos Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Department of English and Creative Writing, Brandeis University, Waltham, MA, United States
| | - Zhen Wei
- Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Zhe Feng
- Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Zhi-Liu Wu
- Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Walid Yassin
- Martinos Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- McLean Hospital, Harvard Medical School, Belmont, MA, United States
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
| | - William S. Stone
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
| | - Yan Lin
- Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Xue-Jun Kong
- Martinos Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
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O'Reilly C, Huberty S, van Noordt S, Desjardins J, Wright N, Scorah J, Webb SJ, Elsabbagh M. EEG functional connectivity in infants at elevated familial likelihood for autism spectrum disorder. Mol Autism 2023; 14:37. [PMID: 37805500 PMCID: PMC10559476 DOI: 10.1186/s13229-023-00570-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 09/29/2023] [Indexed: 10/09/2023] Open
Abstract
BACKGROUND Many studies have reported that autism spectrum disorder (ASD) is associated with atypical structural and functional connectivity. However, we know relatively little about the development of these differences in infancy. METHODS We used a high-density electroencephalogram (EEG) dataset pooled from two independent infant sibling cohorts, to characterize such neurodevelopmental deviations during the first years of life. EEG was recorded at 6 and 12 months of age in infants at typical (N = 92) or elevated likelihood for ASD (N = 90), determined by the presence of an older sibling with ASD. We computed the functional connectivity between cortical sources of EEG during video watching using the corrected imaginary part of phase-locking values. RESULTS Our main analysis found no significant association between functional connectivity and ASD, showing only significant effects for age, sex, age-sex interaction, and site. Given these null results, we performed an exploratory analysis and observed, at 12 months, a negative correlation between functional connectivity and ADOS calibrated severity scores for restrictive and repetitive behaviors (RRB). LIMITATIONS The small sample of ASD participants inherent to sibling studies limits diagnostic group comparisons. Also, results from our secondary exploratory analysis should be considered only as potential relationships to further explore, given their increased vulnerability to false positives. CONCLUSIONS These results are inconclusive concerning an association between EEG functional connectivity and ASD in infancy. Exploratory analyses provided preliminary support for a relationship between RRB and functional connectivity specifically, but these preliminary observations need corroboration on larger samples.
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Affiliation(s)
- Christian O'Reilly
- Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA.
- Artificial Intelligence Institute of South Carolina, University of South Carolina, 1112 Greene St, Columbia, SC, 29208, USA.
- Carolina Autism and Neurodevelopment Research Center, University of South Carolina, Columbia, SC, USA.
| | - Scott Huberty
- Azrieli Centre for Autism Research, Montreal Neurological Institute-Hospital, McGill University, Montreal, Canada
| | - Stefon van Noordt
- Department of Psychology, Mount Saint Vincent University, Halifax, NS, Canada
| | | | - Nicky Wright
- Department of Psychology, Manchester Metropolitan University, Manchester, UK
| | - Julie Scorah
- Azrieli Centre for Autism Research, Montreal Neurological Institute-Hospital, McGill University, Montreal, Canada
| | | | - Mayada Elsabbagh
- Azrieli Centre for Autism Research, Montreal Neurological Institute-Hospital, McGill University, Montreal, Canada
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7
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Chen WX, Liu X, Huang Z, Guo C, Feng F, Zhang Y, Gao Y, Zheng K, Huang J, Yu J, Wei W, Liang S. Autistic clinical profiles, age at first concern, and diagnosis among children with autism spectrum disorder. Front Psychiatry 2023; 14:1211684. [PMID: 37663609 PMCID: PMC10469837 DOI: 10.3389/fpsyt.2023.1211684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 07/25/2023] [Indexed: 09/05/2023] Open
Abstract
Background To explore the relationship between autistic clinical profiles and age at first concern and diagnosis among children with autism spectrum disorder. The clinical profiles included the severity of autism, cognition, adaptability, language development, and regression. Methods The multivariate linear regression model was used to examine the association of diagnostic age and first-concern age with autistic clinical profiles and with further stratification analysis. Results A total of 801 autistic children were included. Language delay and regression were associated with earlier diagnostic age (language delay: crudeβ: -0.80, 95%CI%: -0.92--0.68; regression: crudeβ: -0.21, 95%CI%: -0.43--0.00) and the age of first concern of autistic children (language delay: crudeβ: -0.55, 95%CI%: -0.65--0.45; regression: crudeβ: -0.17, 95%CI%: -0.34--0.00). After stratification by sex, language delay tended to be more associated with the earlier diagnostic age among boys (crudeβ: -0.85, 95%CI%: -0.98--0.72) than among girls (crudeβ: -0.46, 95%CI%: -0.77--0.16). After stratification by maternal education level or family income level, language delay was most associated with the earlier diagnostic age in autistic children from families with higher socioeconomic levels. Conclusion Language delay, rather than other symptoms, promoted an earlier diagnostic age. Among male autistic children or children from families with higher socioeconomic levels, language delay was most significantly associated with an earlier age of diagnosis. Cognitive delay, or adaptive delay, was associated with a later age at diagnosis and presented only in autistic children from families with lower socioeconomic levels. There may be sex or socioeconomic inequality in the diagnostic age for autistic children. More publicity and public education about the diversity of autistic symptoms are urgently needed in the future, especially for low-socioeconomic families.
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Affiliation(s)
- Wen-Xiong Chen
- Department of Neurology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- The Assessment and Intervention Center for Autistic Children, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- Department of Child Psychology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Xian Liu
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- Department of Children's and Adolescent Health, College of Public Health, Harbin Medical University, Harbin, China
| | - Zhifang Huang
- Department of Neurology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- The Assessment and Intervention Center for Autistic Children, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Cheng Guo
- Department of Neurology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- The Assessment and Intervention Center for Autistic Children, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Fangmei Feng
- Department of Neurology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- The Assessment and Intervention Center for Autistic Children, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Yani Zhang
- Department of Neurology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- The Assessment and Intervention Center for Autistic Children, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Yuanyuan Gao
- Department of Neurology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Kelu Zheng
- Department of Neurology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- The Assessment and Intervention Center for Autistic Children, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Jingyu Huang
- Department of Neurology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- The Assessment and Intervention Center for Autistic Children, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Jing Yu
- The Assessment and Intervention Center for Autistic Children, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- Department of Child Psychology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Wenqing Wei
- The Assessment and Intervention Center for Autistic Children, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- Department of Child Psychology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Simin Liang
- Department of Neurology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- The Assessment and Intervention Center for Autistic Children, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
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Malachowski LG, Huntley MA, Needham AW. Case report: An evaluation of early motor skills in an infant later diagnosed with autism. Front Psychiatry 2023; 14:1205532. [PMID: 37404715 PMCID: PMC10315836 DOI: 10.3389/fpsyt.2023.1205532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 05/29/2023] [Indexed: 07/06/2023] Open
Abstract
Researchers and clinicians are increasingly interested in understanding the etiology of autism spectrum disorder (ASD) and identifying behaviors that can provide opportunities for earlier detection and therefore earlier onset of intervention activities. One promising avenue of research lies in the early development of motor skills. The present study compares the motor and object exploration behaviors of an infant later diagnosed with ASD (T.I.) with the same skills in a control infant (C.I.). There were notable difference in fine motor skills by just 3 months of age, one of the earliest fine motor differences reported in the literature. In line with previous findings, T.I. and C.I. demonstrated different patterns of visual attention as early as 2.5 months of age. At later visits to the lab, T.I. engaged in unique problem-solving behaviors not demonstrated by the experimenter (i.e., emulation). Overall, findings suggest that infants later diagnosed with ASD may show differences in fine motor skills and visual attention to objects from the first months of life.
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Affiliation(s)
- Lauren G. Malachowski
- Department of Psychology and Human Development, Vanderbilt University, Nashville, TN, United States
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Alhassan S, Soudani A, Almusallam M. Energy-Efficient EEG-Based Scheme for Autism Spectrum Disorder Detection Using Wearable Sensors. SENSORS (BASEL, SWITZERLAND) 2023; 23:2228. [PMID: 36850829 PMCID: PMC9962521 DOI: 10.3390/s23042228] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 02/06/2023] [Accepted: 02/15/2023] [Indexed: 06/15/2023]
Abstract
The deployment of wearable wireless systems that collect physiological indicators to aid in diagnosing neurological disorders represents a potential solution for the new generation of e-health systems. Electroencephalography (EEG), a recording of the brain's electrical activity, is a promising physiological test for the diagnosis of autism spectrum disorders. It can identify the abnormalities of the neural system that are associated with autism spectrum disorders. However, streaming EEG samples remotely for classification can reduce the wireless sensor's lifespan and creates doubt regarding the application's feasibility. Therefore, decreasing data transmission may conserve sensor energy and extend the lifespan of wireless sensor networks. This paper suggests the development of a sensor-based scheme for early age autism detection. The proposed scheme implements an energy-efficient method for signal transformation allowing relevant feature extraction for accurate classification using machine learning algorithms. The experimental results indicate an accuracy of 96%, a sensitivity of 100%, and around 95% of F1 score for all used machine learning models. The results also show that our scheme energy consumption is 97% lower than streaming the raw EEG samples.
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Affiliation(s)
- Sarah Alhassan
- Department of Computer Science, College of Computer and Information Science, King Saud University, Riyadh 11362, Saudi Arabia
- Department of Computer Science, College of Computer and Information Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 11564, Saudi Arabia
| | - Adel Soudani
- Department of Computer Science, College of Computer and Information Science, King Saud University, Riyadh 11362, Saudi Arabia
| | - Manan Almusallam
- Department of Computer Science, College of Computer and Information Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 11564, Saudi Arabia
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10
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Delgado CF, Simpson EA, Zeng G, Delgado RE, Miron O. Newborn Auditory Brainstem Responses in Children with Developmental Disabilities. J Autism Dev Disord 2023; 53:776-788. [PMID: 34181140 PMCID: PMC9549590 DOI: 10.1007/s10803-021-05126-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/01/2021] [Indexed: 12/30/2022]
Abstract
We integrated data from a newborn hearing screening database and a preschool disability database to examine the relationship between newborn click evoked auditory brainstem responses (ABRs) and developmental disabilities. This sample included children with developmental delay (n = 2992), speech impairment (SI, n = 905), language impairment (n = 566), autism spectrum disorder (ASD, n = 370), and comparison children (n = 128,181). We compared the phase of the ABR waveform, a measure of sound processing latency, across groups. Children with SI and children with ASD had greater newborn ABR phase values than both the comparison group and the developmental delay group. Newborns later diagnosed with SI or ASD have slower neurological responses to auditory stimuli, suggesting sensory differences at birth.
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Affiliation(s)
- Christine F Delgado
- Department of Psychology, University of Miami, PO Box 248185, Coral Gables, FL, 33124-0721, USA.
| | - Elizabeth A Simpson
- Department of Psychology, University of Miami, PO Box 248185, Coral Gables, FL, 33124-0721, USA
| | - Guangyu Zeng
- Department of Psychology, University of Miami, PO Box 248185, Coral Gables, FL, 33124-0721, USA
| | - Rafael E Delgado
- Biomedical Engineering, University of Miami, Coral Gables, FL, USA
- Intelligent Hearing Systems Corp., Miami, FL, USA
| | - Oren Miron
- Department of Health Systems Management, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Department of Biomedical-Informatics, Harvard Medical School, Boston, MA, USA
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11
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Hadders‐Algra M. Emerging signs of autism spectrum disorder in infancy: Putative neural substrate. Dev Med Child Neurol 2022; 64:1344-1350. [PMID: 35801808 PMCID: PMC9796067 DOI: 10.1111/dmcn.15333] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 06/06/2022] [Accepted: 06/07/2022] [Indexed: 12/30/2022]
Abstract
Autism spectrum disorder (ASD) is characterized by altered development of the social brain with prominent atypical features in the fronto-temporo-parietal cortex and cerebellum. Early signs of ASD emerge between 6 and 12 months: reduced social communication, slightly less advanced motor development, and repetitive behaviour. The fronto-temporo-parietal cortex and cerebellum play a prominent role in the development of social communication, whereas fronto-parietal-cerebellar networks are involved in the planning of movements, that is, movement selection. Atypical sensory responsivity, a core feature of ASD, may result in impaired development of social communication and motor skills and/or selection of atypical repetitive behaviour. In the first postnatal year, the brain areas involved are characterized by gradual dissolution of temporary structures: the fronto-temporo-parietal cortical subplate and cerebellar external granular layer. It is hypothesized that altered dissolution of the transient structures opens the window for the expression of early signs of ASD arising in the impaired developing permanent networks. WHAT THIS PAPER ADDS: The early social and motor signs of autism spectrum disorder emerge between the ages of 6 and 12 months. Altered dissolution of transient brain structures in the fronto-temporo-parietal cortex and cerebellum may underlie the emergence of these early signs.
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Affiliation(s)
- Mijna Hadders‐Algra
- University of Groningen, University Medical Center GroningenDepartment of Paediatrics, Section of Developmental NeurologyGroningenthe Netherlands,University of Groningen, Faculty of Theology and Religious StudiesGroningenthe Netherlands
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12
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Ayoub MJ, Keegan L, Tager-Flusberg H, Gill SV. Neuroimaging Techniques as Descriptive and Diagnostic Tools for Infants at Risk for Autism Spectrum Disorder: A Systematic Review. Brain Sci 2022; 12:602. [PMID: 35624989 PMCID: PMC9139416 DOI: 10.3390/brainsci12050602] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 04/26/2022] [Accepted: 04/27/2022] [Indexed: 02/04/2023] Open
Abstract
Autism Spectrum Disorder (ASD) has traditionally been evaluated and diagnosed via behavioral assessments. However, increasing research suggests that neuroimaging as early as infancy can reliably identify structural and functional differences between autistic and non-autistic brains. The current review provides a systematic overview of imaging approaches used to identify differences between infants at familial risk and without risk and predictive biomarkers. Two primary themes emerged after reviewing the literature: (1) neuroimaging methods can be used to describe structural and functional differences between infants at risk and infants not at risk for ASD (descriptive), and (2) neuroimaging approaches can be used to predict ASD diagnosis among high-risk infants and developmental outcomes beyond infancy (predicting later diagnosis). Combined, the articles highlighted that several neuroimaging studies have identified a variety of neuroanatomical and neurological differences between infants at high and low risk for ASD, and among those who later receive an ASD diagnosis. Incorporating neuroimaging into ASD evaluations alongside traditional behavioral assessments can provide individuals with earlier diagnosis and earlier access to supportive resources.
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Affiliation(s)
- Maria J. Ayoub
- College of Health and Rehabilitation Sciences: Sargent College, Boston University, 635 Commonwealth Avenue, Boston, MA 02215, USA; (M.J.A.); (L.K.)
| | - Laura Keegan
- College of Health and Rehabilitation Sciences: Sargent College, Boston University, 635 Commonwealth Avenue, Boston, MA 02215, USA; (M.J.A.); (L.K.)
| | - Helen Tager-Flusberg
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA;
| | - Simone V. Gill
- College of Health and Rehabilitation Sciences: Sargent College, Boston University, 635 Commonwealth Avenue, Boston, MA 02215, USA; (M.J.A.); (L.K.)
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13
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Shuffrey LC, Pini N, Potter M, Springer P, Lucchini M, Rayport Y, Sania A, Firestein M, Brink L, Isler JR, Odendaal H, Fifer WP. Aperiodic electrophysiological activity in preterm infants is linked to subsequent autism risk. Dev Psychobiol 2022; 64:e22271. [PMID: 35452546 PMCID: PMC9169229 DOI: 10.1002/dev.22271] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 01/31/2022] [Accepted: 03/04/2022] [Indexed: 12/31/2022]
Abstract
Approximately 7% of preterm infants receive an autism spectrum disorder (ASD) diagnosis. Yet, there is a significant gap in the literature in identifying prospective markers of neurodevelopmental risk in preterm infants. The present study examined two electroencephalography (EEG) parameters during infancy, absolute EEG power and aperiodic activity of the power spectral density (PSD) slope, in association with subsequent autism risk and cognitive ability in a diverse cohort of children born preterm in South Africa. Participants were 71 preterm infants born between 25 and 36 weeks gestation (34.60 ± 2.34 weeks). EEG was collected during sleep between 39 and 41 weeks postmenstrual age adjusted (40.00 ± 0.42 weeks). The Bayley Scales of Infant Development and Brief Infant Toddler Social Emotional Assessment (BITSEA) were administered at approximately 3 years of age adjusted (34 ± 2.7 months). Aperiodic activity, but not the rhythmic oscillatory activity, at multiple electrode sites was associated with subsequent increased autism risk on the BITSEA at three years of age. No associations were found between the PSD slope or absolute EEG power and cognitive development. Our findings highlight the need to examine potential markers of subsequent autism risk in high-risk populations other than infants at familial risk.
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Affiliation(s)
- Lauren C Shuffrey
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York, USA.,Division of Developmental Neuroscience, New York State Psychiatric Institute, New York, New York, USA
| | - Nicolò Pini
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York, USA.,Division of Developmental Neuroscience, New York State Psychiatric Institute, New York, New York, USA
| | - Mandy Potter
- Department of Obstetrics and Gynaecology, Stellenbosch University, Tygerberg, Western Cape, South Africa
| | - Priscilla Springer
- Paediatrics and Child Health, Stellenbosch University, Tygerberg, Western Cape, South Africa
| | - Maristella Lucchini
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York, USA.,Division of Developmental Neuroscience, New York State Psychiatric Institute, New York, New York, USA
| | - Yael Rayport
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York, USA
| | - Ayesha Sania
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York, USA.,Division of Developmental Neuroscience, New York State Psychiatric Institute, New York, New York, USA
| | - Morgan Firestein
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York, USA.,Division of Developmental Neuroscience, New York State Psychiatric Institute, New York, New York, USA
| | - Lucy Brink
- Department of Obstetrics and Gynaecology, Stellenbosch University, Tygerberg, Western Cape, South Africa
| | - Joseph R Isler
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York, USA
| | - Hein Odendaal
- Department of Obstetrics and Gynaecology, Stellenbosch University, Tygerberg, Western Cape, South Africa
| | - William P Fifer
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York, USA.,Division of Developmental Neuroscience, New York State Psychiatric Institute, New York, New York, USA.,Department of Pediatrics, Columbia University Irving Medical Center, New York, New York, USA
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14
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Clairmont C, Wang J, Tariq S, Sherman HT, Zhao M, Kong XJ. The Value of Brain Imaging and Electrophysiological Testing for Early Screening of Autism Spectrum Disorder: A Systematic Review. Front Neurosci 2022; 15:812946. [PMID: 35185452 PMCID: PMC8851356 DOI: 10.3389/fnins.2021.812946] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 12/09/2021] [Indexed: 11/13/2022] Open
Abstract
Given the significance of validating reliable tests for the early detection of autism spectrum disorder (ASD), this systematic review aims to summarize available evidence of neuroimaging and neurophysiological changes in high-risk infants to improve ASD early diagnosis. We included peer-reviewed, primary research in English published before May 21, 2021, involving the use of magnetic resonance imaging (MRI), electroencephalogram (EEG), or functional near-infrared spectroscopy (fNIRS) in children with high risk for ASD under 24 months of age. The main exclusion criteria includes diagnosis of a genetic disorder and gestation age of less the 36 weeks. Online research was performed on PubMed, Web of Science, PsycINFO, and CINAHL. Article selection was conducted by two reviewers to minimize bias. This research was funded by Massachusetts General Hospital Sundry funding. IRB approval was not submitted as it was deemed unnecessary. We included 75 primary research articles. Studies showed that high-risk infants had divergent developmental trajectories for fractional anisotropy and regional brain volumes, increased CSF volume, and global connectivity abnormalities on MRI, decreased sensitivity for familiar faces, atypical lateralization during facial and auditory processing, and different spectral powers across multiple band frequencies on EEG, and distinct developmental trajectories in functional connectivity and regional oxyhemoglobin concentrations in fNIRS. These findings in infants were found to be correlated with the core ASD symptoms and diagnosis at toddler age. Despite the lack of quantitative analysis of the research database, neuroimaging and electrophysiological biomarkers have promising value for the screening of ASD as early as infancy with high accuracy, which warrants further investigation.
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Affiliation(s)
- Cullen Clairmont
- Synapse Lab, Athinoula A. Martinos Center, Massachusetts General Hospital, Boston, MA, United States
| | - Jiuju Wang
- Synapse Lab, Athinoula A. Martinos Center, Massachusetts General Hospital, Boston, MA, United States
- NHC Key Laboratory of Mental Health, National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
| | - Samia Tariq
- Synapse Lab, Athinoula A. Martinos Center, Massachusetts General Hospital, Boston, MA, United States
| | - Hannah Tayla Sherman
- Synapse Lab, Athinoula A. Martinos Center, Massachusetts General Hospital, Boston, MA, United States
| | - Mingxuan Zhao
- Department of Business Analytics, Bentley University, Waltham, MA, United States
| | - Xue-Jun Kong
- Synapse Lab, Athinoula A. Martinos Center, Massachusetts General Hospital, Boston, MA, United States
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, United States
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15
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Key AP, Yan Y, Metelko M, Chang C, Kang H, Pilkington J, Corbett BA. Greater Social Competence Is Associated With Higher Interpersonal Neural Synchrony in Adolescents With Autism. Front Hum Neurosci 2022; 15:790085. [PMID: 35069156 PMCID: PMC8770262 DOI: 10.3389/fnhum.2021.790085] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 12/16/2021] [Indexed: 11/22/2022] Open
Abstract
Difficulty engaging in reciprocal social interactions is a core characteristic of autism spectrum disorder. The mechanisms supporting effective dynamic real-time social exchanges are not yet well understood. This proof-of-concept hyperscanning electroencephalography study examined neural synchrony as the mechanism supporting interpersonal social interaction in 34 adolescents with autism spectrum disorder (50% female), age 10-16 years, paired with neurotypical confederates of similar age. The degree of brain-to-brain neural synchrony was quantified at temporo-parietal scalp locations as the circular correlation of oscillatory amplitudes in theta, alpha, and beta frequency bands while the participants engaged in a friendly conversation. In line with the hypotheses, interpersonal neural synchrony was significantly greater during the social interaction compared to the baseline. Lower levels of synchrony were associated with increased behavioral symptoms of social difficulties. With regard to sex differences, we found evidence for stronger interpersonal neural synchrony during conversation than baseline in females with autism, but not in male participants, for whom such condition differences did not reach statistical significance. This study established the feasibility of hyperscanning during real-time social interactions as an informative approach to examine social competence in autism, demonstrated that neural coordination of activity between the interacting brains may contribute to social behavior, and offered new insights into sex-related variability in social functioning in individuals with autism spectrum disorders.
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Affiliation(s)
- Alexandra P. Key
- Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN, United States,Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, United States,*Correspondence: Alexandra P. Key
| | - Yan Yan
- Vanderbilt University, Nashville, TN, United States
| | - Mary Metelko
- Institute for Software Integrated Systems, Vanderbilt University, Nashville, TN, United States
| | - Catie Chang
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States
| | - Hakmook Kang
- Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN, United States,Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Jennifer Pilkington
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Blythe A. Corbett
- Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN, United States,Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
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16
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Aykan S, Puglia MH, Kalaycıoğlu C, Pelphrey KA, Tuncalı T, Nalçacı E. Right Anterior Theta Hypersynchrony as a Quantitative Measure Associated with Autistic Traits and K-Cl Cotransporter KCC2 Polymorphism. J Autism Dev Disord 2022; 52:61-72. [PMID: 33635423 DOI: 10.1007/s10803-021-04924-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/10/2021] [Indexed: 10/22/2022]
Abstract
Our aim was to use theta coherence as a quantitative trait to investigate the relation of the polymorphisms in NKCC1 (rs3087889) and KCC2 (rs9074) channel protein genes to autistic traits (AQ) in neurotypicals. Coherence values for candidate connection regions were calculated from eyes-closed resting EEGs in two independent groups. Hypersynchrony within the right anterior region was related to AQ in both groups (p < 0.05), and variability in this hypersynchrony was related to the rs9074 polymorphism in the total group (p < 0.05). In conclusion, theta hypersynchrony within the right anterior region during eyes-closed rest can be considered a quantitative measure for autistic traits. Replicating our findings in two independent populations with different backgrounds strengthens the validity of the current study.
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Affiliation(s)
- Simge Aykan
- Department of Physiology, Ankara University School of Medicine, Ankara, Turkey.
| | - Meghan H Puglia
- Department of Neurology, University of Virginia, Charlottesville, VA, USA
- Department of Psychology, University of Virginia, Charlottesville, VA, USA
| | - Canan Kalaycıoğlu
- Department of Physiology, Ankara University School of Medicine, Ankara, Turkey
| | - Kevin A Pelphrey
- Department of Neurology, University of Virginia, Charlottesville, VA, USA
| | - Timur Tuncalı
- Department of Medical Genetics, Ankara University School of Medicine, Ankara, Turkey
| | - Erhan Nalçacı
- Department of Physiology, Ankara University School of Medicine, Ankara, Turkey
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17
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Peck FC, Gabard-Durnam LJ, Wilkinson CL, Bosl W, Tager-Flusberg H, Nelson CA. Prediction of autism spectrum disorder diagnosis using nonlinear measures of language-related EEG at 6 and 12 months. J Neurodev Disord 2021; 13:57. [PMID: 34847887 PMCID: PMC8903497 DOI: 10.1186/s11689-021-09405-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 11/05/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Early identification of autism spectrum disorder (ASD) provides an opportunity for early intervention and improved developmental outcomes. The use of electroencephalography (EEG) in infancy has shown promise in predicting later ASD diagnoses and in identifying neural mechanisms underlying the disorder. Given the high co-morbidity with language impairment, we and others have speculated that infants who are later diagnosed with ASD have altered language learning, including phoneme discrimination. Phoneme learning occurs rapidly in infancy, so altered neural substrates during the first year of life may serve as early, accurate indicators of later autism diagnosis. METHODS Using EEG data collected at two different ages during a passive phoneme task in infants with high familial risk for ASD, we compared the predictive accuracy of a combination of feature selection and machine learning models at 6 months (during native phoneme learning) and 12 months (after native phoneme learning), and we identified a single model with strong predictive accuracy (100%) for both ages. Samples at both ages were matched in size and diagnoses (n = 14 with later ASD; n = 40 without ASD). Features included a combination of power and nonlinear measures across the 10‑20 montage electrodes and 6 frequency bands. Predictive features at each age were compared both by feature characteristics and EEG scalp location. Additional prediction analyses were performed on all EEGs collected at 12 months; this larger sample included 67 HR infants (27 HR-ASD, 40 HR-noASD). RESULTS Using a combination of Pearson correlation feature selection and support vector machine classifier, 100% predictive diagnostic accuracy was observed at both 6 and 12 months. Predictive features differed between the models trained on 6- versus 12-month data. At 6 months, predictive features were biased to measures from central electrodes, power measures, and frequencies in the alpha range. At 12 months, predictive features were more distributed between power and nonlinear measures, and biased toward frequencies in the beta range. However, diagnosis prediction accuracy substantially decreased in the larger, more behaviorally heterogeneous 12-month sample. CONCLUSIONS These results demonstrate that speech processing EEG measures can facilitate earlier identification of ASD but emphasize the need for age-specific predictive models with large sample sizes to develop clinically relevant classification algorithms.
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Affiliation(s)
- Fleming C Peck
- Division of Developmental Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, 08544, USA
| | - Laurel J Gabard-Durnam
- Division of Developmental Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
- Department of Psychology, Northeastern University, Boston, MA, 02118, USA
| | - Carol L Wilkinson
- Division of Developmental Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
| | - William Bosl
- Computational Health Informatics Program, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
- Health Informatics Program, University of San Francisco, San Francisco, CA, 94117, USA
| | - Helen Tager-Flusberg
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, 02215, USA
| | - Charles A Nelson
- Division of Developmental Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
- Harvard Graduate School of Education, Cambridge, MA, 02138, USA
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18
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Nadeem MS, Hosawi S, Alshehri S, Ghoneim MM, Imam SS, Murtaza BN, Kazmi I. Symptomatic, Genetic, and Mechanistic Overlaps between Autism and Alzheimer's Disease. Biomolecules 2021; 11:1635. [PMID: 34827633 PMCID: PMC8615882 DOI: 10.3390/biom11111635] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 10/26/2021] [Accepted: 11/01/2021] [Indexed: 02/02/2023] Open
Abstract
Autism spectrum disorder (ASD) and Alzheimer's disease (AD) are neurodevelopmental and neurodegenerative disorders affecting two opposite ends of life span, i.e., childhood and old age. Both disorders pose a cumulative threat to human health, with the rate of incidences increasing considerably worldwide. In the context of recent developments, we aimed to review correlated symptoms and genetics, and overlapping aspects in the mechanisms of the pathogenesis of ASD and AD. Dementia, insomnia, and weak neuromuscular interaction, as well as communicative and cognitive impairments, are shared symptoms. A number of genes and proteins linked with both disorders have been tabulated, including MECP2, ADNP, SCN2A, NLGN, SHANK, PTEN, RELN, and FMR1. Theories about the role of neuron development, processing, connectivity, and levels of neurotransmitters in both disorders have been discussed. Based on the recent literature, the roles of FMRP (Fragile X mental retardation protein), hnRNPC (heterogeneous ribonucleoprotein-C), IRP (Iron regulatory proteins), miRNAs (MicroRNAs), and α-, β0, and γ-secretases in the posttranscriptional regulation of cellular synthesis and processing of APP (amyloid-β precursor protein) have been elaborated to describe the parallel and overlapping routes and mechanisms of ASD and AD pathogenesis. However, the interactive role of genetic and environmental factors, oxidative and metal ion stress, mutations in the associated genes, and alterations in the related cellular pathways in the development of ASD and AD needs further investigation.
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Affiliation(s)
- Muhammad Shahid Nadeem
- Department of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia; (M.S.N.); (S.H.)
| | - Salman Hosawi
- Department of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia; (M.S.N.); (S.H.)
| | - Sultan Alshehri
- Department of Pharmaceutics, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (S.A.); (S.S.I.)
| | - Mohammed M. Ghoneim
- Department of Pharmacy Practice, College of Pharmacy, AlMaarefa University, Ad Diriyah 13713, Saudi Arabia;
| | - Syed Sarim Imam
- Department of Pharmaceutics, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (S.A.); (S.S.I.)
| | - Bibi Nazia Murtaza
- Department of Zoology, Abbottabad University of Science and Technology (AUST), Abbottabad 22310, Pakistan;
| | - Imran Kazmi
- Department of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia; (M.S.N.); (S.H.)
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19
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Zhang H, Wang C, Yang T, Phua KS, Ng VSH, Law ECN. Infant EEG Band Power Analysis at 6 Months and 18 Months. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:6353-6356. [PMID: 34892566 DOI: 10.1109/embc46164.2021.9629872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Neural development of infants has drawn increasing research interests from the community. In this paper, we investigated the frequency band power of 112 infants who participated in an auditory oddball experiment, and the visual expectation (VE) score of 177 infants who went through a visual expectation paradigm test. Analysis found that the frequency band power decreases in the delta and theta bands, and increases in the alpha and beta bands when the infants grow up from 6 months old to 18 months old. We also proposed a sustainability index to measure the capability of a subject to maintain their band power in the auditory oddball experiment when infants grow up from 6 months old to 18 months old. Analysis shows that the sustainability index increased significantly in the alpha and beta band, decreased in the delta and theta bands. Correlation between the VE score and frequency band power was investigated on 47 infants who participated in both auditory oddball experiment and visual expectation paradigm test. Analysis shows that the reaction speed to stimulus have statistical a significant correlation with the changes of band power and sustainability index in posterior and temporal section, and in the higher frequency bands.
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20
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McDonald NM, Jeste SS. Beyond Baby Siblings-Expanding the Definition of "High-Risk Infants" in Autism Research. Curr Psychiatry Rep 2021; 23:34. [PMID: 33860866 PMCID: PMC8765326 DOI: 10.1007/s11920-021-01243-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/24/2021] [Indexed: 12/12/2022]
Abstract
PURPOSE OF REVIEW Much of our understanding of early development in children with autism spectrum disorder (ASD) comes from studies of children with a family history of autism. We reviewed the current literature on neurodevelopmental profiles and autism prevalence from other high-risk infant groups to expose gaps and inform next steps. We focused on infants with early medical risk (e.g., preterm birth) and genetic risk (tuberous sclerosis complex [TSC]). RECENT FINDINGS About 7% of very preterm infants are later diagnosed with ASD. Prospective studies of early development outside of familial-risk infants are rare; however, recent work within preterm and TSC infants suggests interesting similarities and differences from infants with a family history of ASD. It is essential that we extend our knowledge of early markers of ASD beyond familial-risk infants to expand our knowledge of autism as it emerges in order to develop better, more individualized early interventions.
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Affiliation(s)
- Nicole M McDonald
- UCLA Semel Institute for Neuroscience and Human Behavior, 760 Westwood Plaza, Los Angeles, CA, 90095, USA.
| | - Shafali S Jeste
- UCLA Semel Institute for Neuroscience and Human Behavior, 760 Westwood Plaza, Los Angeles, CA, 90095, USA
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