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. 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. 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.

A Novel Way to Measure and Predict Development: A Heuristic Approach to Facilitate the Early Detection of Neurodevelopmental Disorders / Marschik, Peter B; Pokorny, Florian B; Peharz, Robert; Zhang, Dajie; O'Muircheartaigh, Jonathan; Roeyers, Herbert; Bölte, Sven; Spittle, Alicia J; Urlesberger, Berndt; Schuller, Björn; Poustka, Luise; Ozonoff, Sally; Pernkopf, Franz; Pock, Thomas; Tammimies, Kristiina; Enzinger, Christian; Krieber, Magdalena; Tomantschger, Iris; Bartl-Pokorny, Katrin D; Sigafoos, Jeff; Roche, Laura; Esposito, Gianluca; Gugatschka, Markus; Nielsen-Saines, Karin; Einspieler, Christa; Kaufmann, Walter E.. - In: CURRENT NEUROLOGY AND NEUROSCIENCE REPORTS. - ISSN 1528-4042. - 2017, 17:5(2017), pp. 43.1-43.15. [10.1007/s11910-017-0748-8]

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

Esposito, Gianluca;
2017-01-01

Abstract

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. 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. 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.
2017
5
Marschik, Peter B; Pokorny, Florian B; Peharz, Robert; Zhang, Dajie; O'Muircheartaigh, Jonathan; Roeyers, Herbert; Bölte, Sven; Spittle, Alicia J; Url...espandi
A Novel Way to Measure and Predict Development: A Heuristic Approach to Facilitate the Early Detection of Neurodevelopmental Disorders / Marschik, Peter B; Pokorny, Florian B; Peharz, Robert; Zhang, Dajie; O'Muircheartaigh, Jonathan; Roeyers, Herbert; Bölte, Sven; Spittle, Alicia J; Urlesberger, Berndt; Schuller, Björn; Poustka, Luise; Ozonoff, Sally; Pernkopf, Franz; Pock, Thomas; Tammimies, Kristiina; Enzinger, Christian; Krieber, Magdalena; Tomantschger, Iris; Bartl-Pokorny, Katrin D; Sigafoos, Jeff; Roche, Laura; Esposito, Gianluca; Gugatschka, Markus; Nielsen-Saines, Karin; Einspieler, Christa; Kaufmann, Walter E.. - In: CURRENT NEUROLOGY AND NEUROSCIENCE REPORTS. - ISSN 1528-4042. - 2017, 17:5(2017), pp. 43.1-43.15. [10.1007/s11910-017-0748-8]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/194337
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