Can we relate machine learning models to brain signals?

Machine learning models are increasingly being used to study cognitive neuroscience or investigate clinical neuroscience questions. However, there are various limitations that can prevent from inferring direct relationships between the obtained model and underlying brain signals. In this talk, we will discuss these limitations with a focus on linear model weights and confounding factors, as well as explore promising avenues of research.