Resting-state fMRI neurodynamics in neuropsychiatric disorders

Neuropsychiatric disorders, such as autism, schizophrenia or epilepsy are neurological diseases that present psychiatric symptoms. Since these mental disorders are at the border between neurology and psychology, they are often ill-defined and the effects of treatment are not always successful. In this research new models were developed for extracting brain dynamics (also called neurodynamics) using functional magnetic resonance imaging (fMRI) from adolescents with autism and elderly with cognitive decline in epilepsy. The models were also applied to study the Mozart effect (cognitive and attention enhancement through intensive listening to Mozart’s music). The dynamics methods used come from different fields of research in dynamic systems, such as financial markets, geophysics and evolutionary game theory. This research shows that using these new image-based brain analysis techniques combined with modern classification (machine learning) algorithms, one can accurately and objectively diagnose autism, or provide informative neurodynamics features in case of cognitive decline in ageing. These results are promising for further developing computer-aided diagnostic tools and the investigation of targeted treatments for neuropsychiatric disorders.

Funded by Maastricht University and Eindhoven University of Technology and Kempenhaeghe Medical Center