A novel way to measure and predict development: A heuristic approach to facilitate the early detection of neurodevelopmental disorders

Peter B. Marschik, Florian B. Pokorny, Robert Peharz, Dajie Zhang, Jonathan O’Muircheartaigh, Herbert Roeyers, Sven Bölte, Alicia J. Spittle, Berndt Urlesberger, Björn Schuller, Luise Poustka, Sally Ozonoff, Franz Pernkopf, Thomas Pock, Kristiina Tammimies, Christian Enzinger, Magdalena Krieber, Iris Tomantschger, Katrin D. Bartl-Pokorny, Jeff SigafoosLaura Roche, Gianluca Esposito, Markus Gugatschka, Karin Nielsen-Saines, Christa Einspieler, Walter E. Kaufmann

Research output: Contribution to journalReview articleAcademicpeer-review

28 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number43
Number of pages15
JournalCurrent Neurology and Neuroscience Reports
Volume17
Issue number5
DOIs
Publication statusPublished - 1 May 2017
Externally publishedYes

Keywords

  • Computer vision
  • Diagnosis
  • Early human development
  • Intelligent vocalisation analysis
  • Multidimensional assessment
  • Neurodevelopmental disorders

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