There is strong behavioral and physiological evidence that the brain both represents
probability distributions and performs probabilistic inference. Computational neuroscientists …

In the generative tradition, the language faculty has been shrinking—perhaps to include only
the mechanism of recursion. This paper argues that even this view of the language faculty is …

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 …

A work that reveals the profound links between the evolution, acquisition, and processing of
language, and proposes a new integrative framework for the language sciences. Language …

Ming Li Paul Vitányi Fourth Edition Page 1 An Introduction to Kolmogorov Complexity and Its
Applications Ming Li Paul Vitányi Fourth Edition Texts in Computer Science Page 2 Texts in …

A 2-layer symbolic network model based on the equilibrium equations of the Rescorla–
Wagner model (Danks, 2003) is proposed. The study first presents 2 experiments in Serbian …

A central debate in cognitive science concerns the nativist hypothesis, the proposal that
universal features of behavior reflect a biologically determined cognitive substrate: For …

It remains unsettled whether human language relies exclusively on innately privileged brain
structure in the left hemisphere or is more flexibly shaped through experiences, which …

Each of our theories of mental representation provides some insight into how the mind
works. However, these insights often seem incompatible, as the debates between symbolic …

Three classifiers from machine learning (the generalized linear mixed model, memory based
learning, and support vector machines) are compared with a naive discriminative learning …