Dr. Marios Philiastides has been awarded €2m over five years to launch the Dynamic Network Reconstruction of Human Perceptual and Reward Learning via Multimodal Data Fusion (DyNeRfusion). The work will focus on how our brains learn to optimise our decisions through training and past experiences, using state-of-the-art brain imaging (fusion on EEG and fMRI) and mathematical modelling of human behaviour. Our team will be working to uncover the processes by which the human brain learns – through trial and error – to make better predictions and plan future actions.
Consider learning to inspect a noisy x-ray image to issue an accurate diagnosis or learning to choose between different stock options to maximize your financial returns. These seemingly disparate learning scenarios have thus far been studied in isolation. Our main aim is to develop a unified framework for understanding the neurological processes underlying learning and decision making across different domains. We hope that the work will help inform future developments in machine learning and artificial intelligence and more specifically, how recent incarnations of artificial neural networks could learn to deal with an ever-increasing number of “big data” applications.
For more details visit: https://erc.europa.eu/news/erc-awards-over-600-million-euro-europes-top-researchers
Meet our team of current and past postgraduate students, post-doctoral fellows and research interns
Discover our research interests and our lab’s general research methodology in multimodal brain imaging
Read our research publications appearing in peer-reviewed journals, book chapters and conference proceedings