Huth's research uses computational methods to model how the brain processes language and represents meaning. He is also interested in fMRI technology and data visualization.
His lab uses quantitative, computational methods to try to understand how the human brain processes the natural world. In particular, they are focused on understanding how the meaning of language is represented in the brain. Using fMRI, they record human brain responses while people listen to speech in the form of stories or podcasts. Then they build encoding models that predict those responses based on the audio and transcript of the stories. The best encoding models today use neural network language models to extract meaningful information from the stories. Their work uses encoding models to map how language is represented across the brain, investigates why neural network language models are so effective, and shows that they can even decode language from fMRI.