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Found 2 papers, 2 papers with code
CLIP-MUSED: CLIP-Guided Multi-Subject Visual Neural Information Semantic Decoding
Although prior multi-subject decoding methods have made significant progress, they still suffer from several limitations, including difficulty in extracting global neural response features, linear scaling of model parameters with the number of subjects, and inadequate characterization of the relationship between neural responses of different subjects to various stimuli.
Multi-view Multi-label Fine-grained Emotion Decoding from Human Brain Activity
Existing emotion decoding methods still have two main limitations: one is only decoding a single emotion category from a brain activity pattern and the decoded emotion categories are coarse-grained, which is inconsistent with the complex emotional expression of human; the other is ignoring the discrepancy of emotion expression between the left and right hemispheres of human brain.
