NeuralBench is a new benchmarking framework for neuroAI models on EEG data that finds foundation models only marginally outperform task-specific ones while many tasks like cognitive decoding stay highly challenging.
arXiv preprint arXiv:2505.14556 , year=
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Linear contrastive decoders outperform ridge regression and non-linear alternatives when mapping fMRI activity to foundation model embeddings in vision, text, and audio.
Augmenting limited fMRI datasets with synthetic responses from TRIBE v2 improves brain-to-image decoding accuracy and can yield above-chance performance using only synthetic data.
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Boosting Brain-to-Image Decoding with TRIBE v2 Data Augmentation
Augmenting limited fMRI datasets with synthetic responses from TRIBE v2 improves brain-to-image decoding accuracy and can yield above-chance performance using only synthetic data.