Network dynamics of visual perceptual learning in the human brain


The human brain is highly flexible, enabling us to learn new skills throughout life. Training can improve performance on a wide range of tasks, probing such diverse processes as motor skills, working memory, attentional capacities and economic decision making to low-level perceptual judgments. In particular, training on basic visual tasks has been shown to induce lasting improvements in performance, a phenomenon called visual learning. For example, radiologists are able to identify fine patterns of tumours in images that show no pattern to the layman. Why is that? Is the radiologist really seeing better? Or is she using the visual information in a more effective way than the layman? And what are the neurophysiological and molecular underpinnings of these changes? The most direct way to answer these fundamental questions is to link changes in the coupling between sensory and decision-related areas of the brain to (i) improvements in behavioural performance during visual learning and (ii) the neurotransmitter systems involved in mediating such neuronal plasticity. The overarching goal of this project is to characterize the large-scale network basis of visual perceptual learning in the human brain. To this end, we use an integrated approach that combines psychophysical and electrophysiological measurements with computational modelling of these data.


Project number


Main applicant

Dr. T.H. Donner

Affiliated with

Universiteit van Amsterdam, Faculteit der Maatschappij- en Gedragswetenschappen, Psychologie


17/01/2018 to 15/02/2019