Figure 1: \\sharpfontCross-dataset visual-fMRI harmonization and the BRAID-fMRI model.a, Visual stimuli are presented during fMRI acquisition, and single-trial responses are estimated to obtain stimulus-specific brain activity patterns. b, Eight visual-fMRI datasets spanning static-image and dynamic-video experiments are brought into a common processing framework. fMRI responses are represented using 360 HCP-MMP1.0 cortical parcels and 19 additional regions, while stimuli are represented in a common 512-dimensional CLIP ViT-B/32 image space. c, ROI-wise responses from participants in eight visual-fMRI datasets are mapped to ROI tokens and augmented with learned ROI embeddings and, in participant-conditioned analyses, learned participant embeddings. A Transformer shared across datasets and participants contextualizes the tokens, which are attention-pooled and projected into the 512-dimensional image space of a frozen CLIP ViT-B/32 encoder. Participant embeddings are omitted in the zero-shot transfer experiments. A multi-positive contrastive objective aligns neural responses with their corresponding stimuli while treating repeated observations of the same stimulus as positives. ### One model retrieves visual stimuli across datasets and participants 出处: Many Brains, One Geometry: A Shared Visual-Semantic Space for Cross-Dataset fMRI Decoding（arXiv）Figure 3: \\sharpfontSemantic organization, network contributions and zero-shot cross-dataset transfer.a, t-SNE visualization of 40 kk-means clusters obtained from normalized CLIP embeddings of unique validation stimuli. Ten clusters used for subsequent analyses are highlighted, with representative stimuli shown. b, Dataset composition of the selected clusters. Stacked bars show the number of unique stimuli contributed by each dataset. Cluster labels (C0–C39) denote arbitrary kk-means cluster identifiers and are unrelated to retrieval rank; ranks indicate ordering by Top-10 retrieval accuracy. c, Top: unique-stimulus Top-10 accuracy for all clusters, ordered by performance; bottom: number of unique stimuli in the same ordering. Every fourth cluster in the ranked sequence was retained, yielding ten clusters spanning the full performance range. d, Global unique-stimulus Top-10 accuracy after masking each functional or anatomical ROI group. The dashed line marks the unablated baseline; annotations give percentage-point changes. e,Dataset-specific ablation effects. f, Participant-level effects for the four most disruptive groups. Points denote participants, violins show distributions, boxes show medians and interquartile ranges, and black circles show means. Asterisks denote one-sided Wilcoxon signed-rank tests of retrieval impairment, with Benjamini–Hochberg correction across nine groups. g, Zero-shot participant and dataset transfer with participant embeddings disabled throughout training and evaluation. For each target, the entire dataset and all of its participants remain held out while source datasets and participants are cumulatively added to pretraining. Values are percentage changes relative to step 0; annotations report the net change from the first to the final step.### A shared visual backbone supports retrieval across datasets 出处: Many Brains, One Geometry: A Shared Visual-Semantic Space for Cross-Dataset fMRI Decoding（arXiv）
