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The Capacity of Thought: Benchmarking Llama 3.2 in Semantic fMRI Neural Language

Decoding continuous language from fMRI signals remains a core challenge in non-invasive brain-computer interface research. We present two complementary investigations. First, we improve the Huth et al. ridge regression encoding pipeline thr

https://arxiv.org/abs/2607.12079v1 ↗
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Milos Suvakovic
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Dom Marhoefer
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Glenn Grant-Richards
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Aidan Pinero
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arXiv The Capacity of Thought: Benchmarking Llama 3.2 in Semantic fMRI Neural Language Decoding and Improving the Huth Encoding-Model Baseline · based on signal ▸

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