The Vision and Imaging Data Analytics group at the Department of Cognitive Science and Artificial Intelligence, Tilburg University uses artificial intelligence and big neuroimaging data to better understand the neural consequences of visual impairment due to ophthalmological disease or neural injury. We develop statistical and machine learning techniques to predict functional vision in daily life, to understand the underlying neurobiological mechanisms of visual cortex plasticity and degeneration on the basis of neuroimaging data, and to develop novel neuroimaging biomarkers for predicting and monitoring the efficacy of ophthalmological treatment and visual rehabilitation. Methodological approaches of interest include:
Connectopic Mapping based on Non-linear Manifold Learning
Population Receptive Field and Connective Field Modelling
Spatial Statistical Modelling to enable quantitative comparisons of functional brain organisation
Normative Modelling for characterising population variation in health and disease
Variance Decomposition methods such as probabilistic and linked ICA
Deep Convolutional Neural Networks for MRI and retinal image analysis.
While we have a particularly strong focus on disorders of the visual system, the methods we develop also have applications in health and many clinical settings, such as: Deep Brain Stimulation, Alzheimer's and Parkinson's Disease, as well as Psychiatric Disorders including Stress, Depression, Autism, and ADHD.