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    A Novel Way to Measure and Predict Development: A Heuristic Approach to Facilitate the Early Detection of Neurodevelopmental Disorders

    Access Status
    Open access via publisher
    Authors
    Marschik, P.
    Pokorny, F.
    Peharz, R.
    Zhang, D.
    O Muircheartaigh, J.
    Roeyers, H.
    Bolte, Sven
    Spittle, A.
    Urlesberger, B.
    Schuller, B.
    Poustka, L.
    Ozonoff, S.
    Pernkopf, F.
    Pock, T.
    Tammimies, K.
    Enzinger, C.
    Krieber, M.
    Tomantschger, I.
    Bartl-Pokorny, K.
    Sigafoos, J.
    Roche, L.
    Esposito, G.
    Gugatschka, M.
    Nielsen-Saines, K.
    Einspieler, C.
    Kaufmann, W.
    Date
    2017
    Type
    Journal Article
    
    Metadata
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    Citation
    Marschik, P. and Pokorny, F. and Peharz, R. and Zhang, D. and O Muircheartaigh, J. and Roeyers, H. and Bolte, S. et al. 2017. A Novel Way to Measure and Predict Development: A Heuristic Approach to Facilitate the Early Detection of Neurodevelopmental Disorders. Current Neurology and Neuroscience Reports. 17 (5).
    Source Title
    Current Neurology and Neuroscience Reports
    DOI
    10.1007/s11910-017-0748-8
    ISSN
    1528-4042
    School
    School of Occ Therapy, Social Work and Speech Path
    URI
    http://hdl.handle.net/20.500.11937/63170
    Collection
    • Curtin Research Publications
    Abstract

    © 2017, The Author(s). Purpose of Review: Substantial research exists focusing on the various aspects and domains of early human development. However, there is a clear blind spot in early postnatal development when dealing with neurodevelopmental disorders, especially those that manifest themselves clinically only in late infancy or even in childhood. Recent Findings: This early developmental period may represent an important timeframe to study these disorders but has historically received far less research attention. We believe that only a comprehensive interdisciplinary approach will enable us to detect and delineate specific parameters for specific neurodevelopmental disorders at a very early age to improve early detection/diagnosis, enable prospective studies and eventually facilitate randomised trials of early intervention. Summary: In this article, we propose a dynamic framework for characterising neurofunctional biomarkers associated with specific disorders in the development of infants and children. We have named this automated detection ‘Fingerprint Model’, suggesting one possible approach to accurately and early identify neurodevelopmental disorders.

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