Neural Representations of Language Meaning

Explore neural representations of language meaning in this seminar by Tom M. Mitchell from Carnegie Mellon University. Delve into machine learning methods used to discover mappings between language features and neural activity observed through fMRI and MEG brain imaging. Learn about neural encodings of word meanings, their subcomponents, and the flow of neurally encoded information during word and sentence comprehension. Gain insights into ongoing research questions and the crucial role of machine learning algorithms in understanding how the human brain creates and represents meanings of words, sentences, and stories.

Introduction
Brain Teaser
Research Agenda
Functional MRI
Training a Classifier
Experiments
Canonical Correlation
Linear Mapping
Feedforward Model
Latent Feature
Temporal Component
Grasping
Size