RJ Antonello
@rjantonello.bsky.social
Postdoc in the Mesgarani Lab. Studying how we can use AI to understand language processing in the brain.
A big effort on the part of all the authors (@csinva.bsky.social, Suna Guo, Gavin Mischler, Jianfeng Gao, Nima Mesgarani, @alexanderhuth.bsky.social) Check out the preprint on bioRXiv here! www.biorxiv.org/content/10.1...
Evaluating scientific theories as predictive models in language neuroscience
Modern data-driven encoding models are highly effective at predicting brain responses to language stimuli. However, these models struggle to explain the underlying phenomena, i.e. what features of the...
www.biorxiv.org
August 18, 2025 at 9:42 AM
A big effort on the part of all the authors (@csinva.bsky.social, Suna Guo, Gavin Mischler, Jianfeng Gao, Nima Mesgarani, @alexanderhuth.bsky.social) Check out the preprint on bioRXiv here! www.biorxiv.org/content/10.1...
We think these QA models are an important step in bridging the gap between data-driven models of the brain and the easy-to-understand, but hard-to-encode, qualitative theories that guide our intuitions as neuroscientists. 5/6
August 18, 2025 at 9:42 AM
We think these QA models are an important step in bridging the gap between data-driven models of the brain and the easy-to-understand, but hard-to-encode, qualitative theories that guide our intuitions as neuroscientists. 5/6
More surprisingly, we find that the model places critical importance on some unexpected topics, like the existence of specialized or technical terminology or on words that describe events like dialogue or direct speech quotations. 4/6
August 18, 2025 at 9:42 AM
More surprisingly, we find that the model places critical importance on some unexpected topics, like the existence of specialized or technical terminology or on words that describe events like dialogue or direct speech quotations. 4/6
Our model naturally and automatically replicates many famous neuroscience results, in addition to opening the door to a few surprises. For instance, we naturally observe the selectivity to tactile sensation words in somatosensory areas, and the selectivity to places in OPA, PPA and RSC. 3/6
August 18, 2025 at 9:42 AM
Our model naturally and automatically replicates many famous neuroscience results, in addition to opening the door to a few surprises. For instance, we naturally observe the selectivity to tactile sensation words in somatosensory areas, and the selectivity to places in OPA, PPA and RSC. 3/6
We show that the model we outperforms less interpretable models built out of the hidden states of LLMs, especially in low data settings. Our model is so compact that it can be fully illustrated in a single figure! 2/6
August 18, 2025 at 9:42 AM
We show that the model we outperforms less interpretable models built out of the hidden states of LLMs, especially in low data settings. Our model is so compact that it can be fully illustrated in a single figure! 2/6