Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).
This approach combined: (1) supervised machine learning for text classification, (2) comparative topic modeling with both theory-driven and data-driven Latent Dirichlet Allocation (LDA) to identify ...
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