It is shown that neurons identified solely from clinical language differences can influence behavior across multiple cognitive domains, providing proof of concept for an AD-related computational phenotype and a controlled framework for experimentally examining links between language and broader cognitive dysfunction.
Rui He, Ercong Nie, Hongxu Jiang et al.· 0 citations
Large language models (LLMs) with human-like performance on linguistic tasks have transformed the study of language in neurodiverse conditions. LLMs provide representations of linguistic input in the form of high-dimensional vectors (embeddings), and next-token predictions computed from these embeddings. Previous cross...
S. Vallisa, C. Palominos, Rui He et al.· 0 citations
The results suggest that brain-LLM alignment is more robust across languages, transformer depth, and model architectures than previously appreciated, but less informative about shared computational mechanisms.
This work investigates the layer-wise evolution of ID, and shows that closed-class items expand earlier and collapse sooner than open-class ones, and recovers a token's grammatical role, and uses them to interpret how the semantic content of each PoS evolves across layers in a downstream classification task.
S. Vallisa, Federico Ravenda, C. Palominos et al.· 0 citations
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