Name: Marco Palma
From: University of Warwick
Title: title: Quantifying uncertainty in brain-predicted age using scalar-on-image quantile regression  
Abstract: abstract: Prediction of subject age from brain anatomical MRI has the potential to provide a sensitive summary of brain changes, indicative of different neurodegenerative diseases. However, existing studies typically neglect the uncertainty of these predictions.

In this work, we take into account this uncertainty by applying methods of functional data analysis. In particular, we propose a penalized functional quantile regression model of age on brain structure with cognitively normal (CN) subjects in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and use it to predict brain age in Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD) subjects. Unlike the machine learning approaches available in the literature of brain age prediction, which provide only point predictions, the outcome of our model is a prediction interval for each subject.

In this talk an overview of all the theoretical aspects (functional data analysis, multidimensional smoothing, quantile regression) will be provided, followed by a discussion of the main results and of their meaning in the field of neuroscience of aging.