Workpackage 4: Neurocognitive Predictors

Workpackage leader

Paolo Brambilla

Paolo Brambilla

Università degli Studi di Milano


Objectives of the Workpackage

Workpackage 4 (WP 4) has two main objectives; the first objective is to examine study participants with a cross-domain neuropsychological test battery at baseline and after 9 months of observation. The second objective is to develop, optimise and cross-validate neurocognitive predictors of clinical endpoints by analysing neurocognitive data with undefinedWP 2 machine learning methods.  

Description of the tasks

WP 4 and its WP lead University of Milan (UMIL) is responsible for the development of the neuropsychological test battery. We will standardise measurements of cross-domain neurocognitive performance by means of a computerized neuropsychological assessment tool which will be distributed to the other partners of PRONIA at the Universities of Munich, Birmingham, Basel, Cologne, Udine, and Turku. Specifically, a fully computerised neuropsychological assessment tool will be implemented for collecting and analysing neurocognitive data, available in English, Finnish, German and Italian. Neurocognitive data acquisition will be collected in all centres at baseline and after 9 months. Beside the standardisation of neuropsychological testing, which will be facilitated by our computerised assessment battery, we will implement procedures to ensure a high quality and reliability of the neuropsychological evaluation throughout the funding period by supplying regular training to clinical neuropsychologists. Then, we will use the neurocognitive data acquired at baseline along with the machine learning systems produced by WP 2 to predict clinical and functional outcomes in our help-seeking cohorts. Finally, we will evaluate whether the machine learning-based analysis of longitudinal neurocognitive information allows for a refinement of prognostic models compared to predictors that only make use of the baseline data


WP 3: Neuroimaging <<

>> WP 5: Genomics


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