GROUNDING MODELS OF LANGUAGE IN THE BRAIN

BRIAN MURPHY

Center for Mind/Brain Sciences, University of Trento

Over recent decades, linguistics has produced an abundance of
theoretical models, while suffering from a lack of empirical
robustness. Judgments elicited from native speakers can provide
nuanced insights into the psychological states underlying
communicative behavior, but are distorted by pervasive cognitive
biases. Corpora (large collections of text) have clear advantages of
authenticity and size, but are divorced from the communicative
context. Recordings of neural activity can provide a happy medium,
giving an objective and direct snapshot of the language faculty in
action, though the data is noisy and contains confounding activations
due to other cognitive processes that typically accompany a language
task. In this talk I will describe work we have carried out here at
CIMeC, which uses machine learning methods to attempt to distinguish
linguistic states and processes in the brain. I will concentrate on
decoding lexical meaning, and in particular deal with the many
systematic perceptual and performance-based confounds that can make
this difficult.

BIO

Brian Murphy is a postdoctoral fellow at the Centre for Mind/Brain
Science, of the University of Trento, Italy. Before moving into
research, he gained a degree in engineering and spent 5 years working
in software development in Germany and China. He holds an M.Phil.
(2001) and Ph.D. (2007) from Trinity College, Dublin, both in
computational linguistics, with an emphasis on language semantics and
its interaction with sentential syntax. Since coming to Trento, his
main topic of research has been word meaning, using machine learning
methods to discover conceptual organization both from large language
corpora and recordings of neural activity (EEG, MEG and fMRI).