Abstract Concreteness ratings are frequently used in a variety of disciplines to operationalize differences between concrete and abstract words and concepts. However, most ratings studies present items in isolation, thereby overlooking the potential polysemy of words. Consequently, ratings for polysemous words may be conflated, causing a threat to the validity of concreteness‐ratings studies. This is […]

Stroke causes behavioral deficits in multiple cognitive domains and there is a growing interest in predicting patient performance from neuroimaging data using machine learning techniques. Here we investigated a deep learning approach based on Convolutional Neural Networks (CNNs) for predicting the severity of language disorder from 3D MRI lesion images from magnetic resonance imaging (MRI) […]

A new approach to understanding the interaction between cortical areas is provided by a mathematical analysis of biased competition, which describes many interactions between cortical areas, including those involved in top-down attention. The analysis helps to elucidate the principles of operation of such cortical systems, and in particular the parameter values within which biased competition […]