Reservoir computing is a computational framework suited for temporal/sequential data
processing. It is derived from several recurrent neural network models, including echo state …

Neural networks, as powerful tools for data mining and knowledge engineering, can learn
from data to build feature‐based classifiers and nonlinear predictive models. Training neural …

Memory is fleeting. New material rapidly obliterates previous material. How, then, can the
brain deal successfully with the continual deluge of linguistic input? We argue that, to deal …

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 …

Developmental machine learning studies how artificial agents can model the way children
learn open-ended repertoires of skills. Such agents need to create and represent goals …

Cortical neural connectivity has been shown to exhibit a small-world (SW) network topology.
However, the role of the topology in neural information processing remains unclear. In this …

Primates display a remarkable ability to adapt to novel situations. Determining what is most
pertinent in these situations is not always possible based only on the current sensory inputs …

This volume is the first handbook dedicated to language attrition, the study of how a
speaker's language may be affected by crosslinguistic interference and non-use. The effects …

Cognitive gadgets are distinctively human cognitive mechanisms–such as imitation, mind
reading, and language–that have been shaped by cultural rather than genetic evolution …

" Introduction There are numerous neurobiological models of language, ranging from those
concerned with speech perception, white matter structure, and the function of dorsal and …