Weizmann dual-branch decoder reconstructs viewed images from 1 mm voxel fMRI in 8 subjects

The system was trained on publicly released high-resolution fMRI datasets where each voxel covers one cubic millimeter. Two parallel branches predict spatial layout and semantic content before feeding a diffusion model. Prior single-branch decoders produced structurally inconsistent outputs even for simple objects such as bananas; the dual-branch approach aligns both position and color statistics.

Earlier fMRI reconstruction studies using 3 mm voxels yielded blurry results that could not preserve object identity or arrangement. The Weizmann dataset improves spatial sampling by a factor of 27. No public ablation shows whether the accuracy gain stems from resolution, the dual-branch architecture, or the specific diffusion scheduler.

Coverage emphasized therapeutic uses for locked-in patients yet omitted the absence of any consent or data-governance protocol for non-clinical deployment. Existing U.S. and EU neuro-rights proposals lack technical thresholds for when decoded output constitutes admissible evidence. Operational deployment therefore hinges on whether voxel-level identifiers can be stripped before model inference.

Next milestones require longitudinal scans of the same subjects plus explicit testing on internally generated imagery rather than external stimuli. Without those controls, claims about dream reconstruction remain untestable.