Neuroscientists have long characterized the properties and functions of the nervous system,
and are increasingly succeeding in answering how brains perform the tasks they do. But the …

Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to
model behavioural and neural data, an approach we call 'neuroconnectionism'. ANNs have …

Deep neural networks (DNNs) have had extraordinary successes in classifying
photographic images of objects and are often described as the best models of biological …

Cognitive Neuroscience of Language provides an up-to-date, wide-ranging, and
pedagogically practical survey of the most important developments in this exciting field. It …

In expert readers, a brain region known as the visual word form area (VWFA) is highly
sensitive to written words, exhibiting a posterior-to-anterior gradient of increasing sensitivity …

Researchers studying the correspondences between Deep Neural Networks (DNNs) and
humans often give little consideration to severe testing when drawing conclusions from …

The morphological structure of complex words impacts how they are processed during
visual word recognition. This impact varies over the course of reading acquisition and for …

Mathematical operations have long been regarded as a sparse, symbolic process in
neuroimaging studies. In contrast, advances in artificial neural networks (ANN) have …

Object recognition is the process by which humans organize the visual world into
meaningful perceptual units. In this Review, we examine the developmental origins and …

Previous research has shown that, unlike misspelled common words, misspelled brand
names are sensitive to visual letter similarity effects (eg, amazom is often recognized as a …