Marschik, Peter B.

[["dc.bibliographiccitation.firstpage","1275"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","Cellular and Molecular Life Sciences : CMLS"],["dc.bibliographiccitation.lastpage","1297"],["dc.bibliographiccitation.volume","76"],["dc.contributor.author","Bölte, Sven"],["dc.contributor.author","Girdler, Sonya"],["dc.contributor.author","Marschik, Peter B."],["dc.date.accessioned","2019-07-09T11:50:34Z"],["dc.date.accessioned","2020-06-23T08:40:25Z"],["dc.date.available","2019-07-09T11:50:34Z"],["dc.date.available","2020-06-23T08:40:25Z"],["dc.date.issued","2019"],["dc.description.abstract","Autism spectrum disorder (ASD) is a neurodevelopmental condition of heterogeneous etiology. While it is widely recognized that genetic and environmental factors and their interactions contribute to autism phenotypes, their precise causal mechanisms remain poorly understood. This article reviews our current understanding of environmental risk factors of ASD and their presumed adverse physiological mechanisms. It comprehensively maps the significance of parental age, teratogenic compounds, perinatal risks, medication, smoking and alcohol use, nutrition, vaccination, toxic exposures, as well as the role of extreme psychosocial factors. Further, we consider the role of potential protective factors such as folate and fatty acid intake. Evidence indicates an increased offspring vulnerability to ASD through advanced maternal and paternal age, valproate intake, toxic chemical exposure, maternal diabetes, enhanced steroidogenic activity, immune activation, and possibly altered zinc-copper cycles and treatment with selective serotonin reuptake inhibitors. Epidemiological studies demonstrate no evidence for vaccination posing an autism risk. It is concluded that future research needs to consider categorical autism, broader autism phenotypes, as well as autistic traits, and examine more homogenous autism variants by subgroup stratification. Our understanding of autism etiology could be advanced by research aimed at disentangling the causal and non-causal environmental effects, both founding and moderating, and gene-environment interplay using twin studies, longitudinal and experimental designs. The specificity of many environmental risks for ASD remains unknown and control of multiple confounders has been limited. Further understanding of the critical windows of neurodevelopmental vulnerability and investigating the fit of multiple hit and cumulative risk models are likely promising approaches in enhancing the understanding of role of environmental factors in the etiology of ASD."],["dc.identifier.doi","10.1007/s00018-018-2988-4"],["dc.identifier.pmid","30570672"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/15967"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/66605"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59800"],["dc.language.iso","de"],["dc.notes.intern","Merged from goescholar"],["dc.relation","info:eu-repo/grantAgreement/EC/FP7/115300/EU//EU-AIMS"],["dc.relation.issn","1420-682X"],["dc.relation.issn","1420-9071"],["dc.relation.orgunit","Campus Laboratory for Advanced Imaging, Microscopy and Spectroscopy"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject.ddc","610"],["dc.title","The contribution of environmental exposure to the etiology of autism spectrum disorder"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","9888"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Scientific Reports"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Reich, Simon"],["dc.contributor.author","Zhang, Dajie"],["dc.contributor.author","Kulvicius, Tomas"],["dc.contributor.author","Bölte, Sven"],["dc.contributor.author","Nielsen-Saines, Karin"],["dc.contributor.author","Pokorny, Florian B."],["dc.contributor.author","Peharz, Robert"],["dc.contributor.author","Poustka, Luise"],["dc.contributor.author","Wörgötter, Florentin"],["dc.contributor.author","Marschik, Peter B."],["dc.date.accessioned","2021-06-01T10:50:43Z"],["dc.date.available","2021-06-01T10:50:43Z"],["dc.date.issued","2021"],["dc.description.abstract","Abstract The past decade has evinced a boom of computer-based approaches to aid movement assessment in early infancy. Increasing interests have been dedicated to develop AI driven approaches to complement the classic Prechtl general movements assessment (GMA). This study proposes a novel machine learning algorithm to detect an age-specific movement pattern, the fidgety movements (FMs), in a prospectively collected sample of typically developing infants. Participants were recorded using a passive, single camera RGB video stream. The dataset of 2800 five-second snippets was annotated by two well-trained and experienced GMA assessors, with excellent inter- and intra-rater reliabilities. Using OpenPose, the infant full pose was recovered from the video stream in the form of a 25-points skeleton. This skeleton was used as input vector for a shallow multilayer neural network (SMNN). An ablation study was performed to justify the network’s architecture and hyperparameters. We show for the first time that the SMNN is sufficient to discriminate fidgety from non-fidgety movements in a sample of age-specific typical movements with a classification accuracy of 88%. The computer-based solutions will complement original GMA to consistently perform accurate and efficient screening and diagnosis that may become universally accessible in daily clinical practice in the future."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2021"],["dc.identifier.doi","10.1038/s41598-021-89347-5"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/86760"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-425"],["dc.relation.eissn","2045-2322"],["dc.rights","CC BY 4.0"],["dc.title","Novel AI driven approach to classify infant motor functions"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Frontiers in Psychiatry"],["dc.bibliographiccitation.volume","13"],["dc.contributor.affiliation","Marschik, Peter B.; 1Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen and Leibniz Science Campus Primate Cognition, Göttingen, Germany"],["dc.contributor.affiliation","Poustka, Luise; 1Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen and Leibniz Science Campus Primate Cognition, Göttingen, Germany"],["dc.contributor.affiliation","Bölte, Sven; 2Department of Women's and Children's Health, Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Karolinska Institutet and Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm County Council, Stockholm, Sweden"],["dc.contributor.affiliation","Roeyers, Herbert; 6Department of Experimental Clinical and Health Psychology, Faculty of Psychology and Educational Sciences, Ghent University, Ghent, Belgium"],["dc.contributor.affiliation","Nordahl-Hansen, Anders; 7Department of Education, ICT and Learning, Østfold University College, Halden, Norway"],["dc.contributor.author","Marschik, Peter B."],["dc.contributor.author","Poustka, Luise"],["dc.contributor.author","Bölte, Sven"],["dc.contributor.author","Roeyers, Herbert"],["dc.contributor.author","Nordahl-Hansen, Anders"],["dc.date.accessioned","2022-05-02T05:02:41Z"],["dc.date.available","2022-05-02T05:02:41Z"],["dc.date.issued","2022-04-15"],["dc.date.updated","2022-04-30T12:33:22Z"],["dc.identifier.doi","10.3389/fpsyt.2022.893305"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/107154"],["dc.language.iso","en"],["dc.relation","SFB 1528: Kognition der Interaktion"],["dc.relation.eissn","1664-0640"],["dc.rights","CC BY 4.0"],["dc.rights.uri","http://creativecommons.org/licenses/by/4.0/"],["dc.title","Editorial: Trajectories in Developmental Disabilities: Infancy–Childhood–Adolescence"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","editorial_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","3685"],["dc.bibliographiccitation.issue","9"],["dc.bibliographiccitation.journal","Journal of Autism and Developmental Disorders"],["dc.bibliographiccitation.lastpage","3694"],["dc.bibliographiccitation.volume","49"],["dc.contributor.author","Zhang, Dajie"],["dc.contributor.author","Krieber-Tomantschger, Iris"],["dc.contributor.author","Poustka, Luise"],["dc.contributor.author","Roeyers, Herbert"],["dc.contributor.author","Sigafoos, Jeff"],["dc.contributor.author","Bölte, Sven"],["dc.contributor.author","Marschik, Peter B."],["dc.contributor.author","Einspieler, Christa"],["dc.date.accessioned","2020-05-26T09:17:09Z"],["dc.date.available","2020-05-26T09:17:09Z"],["dc.date.issued","2019"],["dc.description.abstract","Identifying the early signs of developmental disability is important for ensuring timely diagnosis and early intervention. Day-care workers may be in a prime position to notice potential developmental deviations, but it is unclear if they can accurately recognize subtle early signs of atypical development. Sixty day-care workers examined home-videos of very young children with fragile X syndrome and typically developing children. Results indicated that most day-care workers can distinguish typical and atypical development in general and might therefore have an important role in early identification. Special work experience and advanced pedagogical training appeared to boost day-care workers’ sensitivity to detect atypical features in early development and to provide effective daily surveillance. Scientific understanding and public awareness of young children at risk for developmental disorders have substantially increased in the past few decades. The growing number of studies on early human development have provided new empirical findings that have altered perspectives on the age-specific phenomena, pathways, and profiles associated with several developmental and genetic disorders (e.g., Johnson et al. 2015; Marschik et al. 2013; Messinger et al. 2013; Thomas et al. 2009). The advancements related to studies on late detected developmental disorders (LDDDs), for example, are particularly evident in research on autism spectrum disorder (ASD; e.g., Bölte et al. 2016, 2013; Bontinck et al. 2018; Bussu et al. 2018; Gliga et al. 2014; Messinger et al. 2013; Roeyers 2018). Research advances have also contributed to what appears to be greater acknowledgment of the significance of earlier detection of atypical development to enable timely intervention and support. In many European countries, as the number of working-mothers keeps climbing, the need of public childcare services increases steadily. In Austria, for example, the proportion of infants and children under 2 years of age who are attending day-care centres doubled from 2007 to 2017. In some urban areas, up to 45% of children aged 0 to 2-years attend day-care, of whom more than 90% spend 6–10 h per day with professional caregivers (Statistik Austria 2018). These day-care workers could thus be seen as among the most important care persons for many young children. As a consequence, it would seem important to investigate the potential role of day-care workers in the early detection of deviant development in young children. For example, might it be feasible to enlist day-care workers in the process of screening children for ASD? Such issues have been highlighted in a number of recent publications (Branson et al. 2008; Dereu et al. 2012; Janus et al. 2018; Janvier et al. 2016; Larsen et al. 2018a, b; Nordahl-Hansen et al. 2018, 2013). Indeed, results from some studies suggest that day-care workers have the competency to accurately report early signs of autism by applying well-designed behavioural checklists (Dereu et al. 2010; Larsen et al. 2018b). There might also be some potential advantages in integrating the help of day-care workers because such personnel often have training and knowledge of early child development and have considerable hands-on experience in working with children of comparable ages and diverse developmental profiles. Given that developmental disabilities affect at least 7 to 9% of young children (Olusanya et al. 2018; Zablotsky et al. 2017), it may be important to involve day-care workers as potential screeners of developmental disability. Unlike parents, day-care workers are likely to be more objective. The input from their daily surveillance may complement to our understanding of the prodromal period of LDDDs and potentially contribute to earlier identification, hence be of important public and scientific interest. Fragile X syndrome (FXS) is one of these LDDDs. Similar to several other disorders, such as Rett syndrome (RTT) and ASD, syndrome related behavioural and physical features are often subtle and elusive to detect at first, which of course makes early identification more challenging. Still, atypical early signs emerging in the first years of life across different developmental domains have been reported to be perceptible to parents of children with FXS (e.g., Hinton et al. 2013; Zhang et al. 2017). Some of these signs are frequently presented and often captured by home videos. With a benchmark procedure retrospectively analysing home videos of children with FXS, we, among other researchers, demonstrated that these signs can be readily identified and classified by professionals (Zhang et al. 2018; see also Baranek et al. 2005). Early phenotypes of FXS present a broad spectrum of atypical neurobehavioural features across various domains (e.g., motor, cognition, speech-language, social-communication), which are not specific to FXS (e.g., Haessler et al. 2016; Hagerman 2002; Kidd et al. 2014; Marschik et al. 2014; Raspa et al. 2017; Roche et al. 2018; Zhang et al. 2017). As early signs of FXS overlap with peculiarities of children with other developmental and genetic disorders, to identify these signs requires sensitivity to deviant development in general and not necessarily expertise in a specific syndrome. Pertinent to the current study, we intended to utilize home-video footage showing behaviours of different developmental areas of typically developing children and children with FXS as material to tap on day-care workers’ general awareness of early development. We adapted a video reviewing procedure used by Burford et al. (2003) by adding benchmark assessments of neurodevelopmental features. Specifically, we aimed to investigate whether day-care workers perceive young children with typical or atypical development differently. In Addition, we intended to find out whether they are able to accurately identify typical and atypical features in early development. As day-care workers have different training and experience backgrounds, we also aimed to answer whether these factors modify day-care workers’ perceptions of early developmental phenomena."],["dc.identifier.doi","10.1007/s10803-019-04056-3"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/16730"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/65978"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.eissn","1573-3432"],["dc.relation.issn","0162-3257"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Identifying Atypical Development: A Role of Day-Care Workers?"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]