Mapping and decoding natural language representations from the human cortex

Brisbane Convention & Exhibition Centre 

Deep neural network language models enable us to model how the human brain responds to natural language with unprecedented accuracy. Applied to very large within-subject datasets, these models enable us to both map language representations with high fidelity and decode language that a person is hearing or thinking from non-invasive functional measurements. I will discuss recent advances in mapping and decoding language representations using BOLD fMRI in combination with modern AI tools and the integration of HD-DOT for these methods.