Generative Visual Grounding creates instance-specific visual proxy images from EEG signals to enhance MLLM understanding of brain activity beyond text-only alignment.
Brain- MAE: A region-aware self-supervised learning framework for brain signals
3 Pith papers cite this work. Polarity classification is still indexing.
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CineNeuron improves fMRI-to-video reconstruction by combining bottom-up semantic enrichment with top-down Mixture-of-Memories integration and outperforms prior methods on benchmarks.
Rhamba uses region-aware masking strategies and hybrid Attention-Mamba models pretrained on ABIDE fMRI data to achieve top AUROC on schizophrenia and ADHD classification tasks while outperforming prior methods.
citing papers explorer
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Visualizing the Invisible: Generative Visual Grounding Empowers Universal EEG Understanding in MLLMs
Generative Visual Grounding creates instance-specific visual proxy images from EEG signals to enhance MLLM understanding of brain activity beyond text-only alignment.
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Bridging Brain and Semantics: A Hierarchical Framework for Semantically Enhanced fMRI-to-Video Reconstruction
CineNeuron improves fMRI-to-video reconstruction by combining bottom-up semantic enrichment with top-down Mixture-of-Memories integration and outperforms prior methods on benchmarks.
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Rhamba: Region-Aware Hybrid Attention-Mamba Framework for Self-Supervised Learning in Resting-State fMRI
Rhamba uses region-aware masking strategies and hybrid Attention-Mamba models pretrained on ABIDE fMRI data to achieve top AUROC on schizophrenia and ADHD classification tasks while outperforming prior methods.