51 citations · 55 across the 12 of their papers we have counts for
4 papers · 1 filter
Advancing credibility and transparency in brain-to-image reconstruction research: Reanalysis of Koide-Majima, Nishimoto, and Majima (Neural Networks, 2024)
Ken Shirakawa, Yoshihiro Nagano, Misato Tanaka +2
A recent high-profile study by Koide-Majima et al. (2024) claimed a major advance in reconstructing visual imagery from brain activity using a novel variant of a generative AI-base…
Readout Representation: Redefining Neural Codes by Input Recovery
Shunsuke Onoo, Yoshihiro Nagano, Yukiyasu Kamitani
Sensory representation is typically understood through a hierarchical-causal framework where progressively abstract features are extracted sequentially. However, this causal view f…
Overcoming Output Dimension Collapse: When Sparsity Enables Zero-shot Brain-to-Image Reconstruction at Small Data Scales
Kenya Otsuka, Yoshihiro Nagano, Yukiyasu Kamitani
Advances in brain-to-image reconstruction are enabling us to externalize the subjective visual experiences encoded in the brain as images. A key challenge in this task is data scar…
Visual Image Reconstruction from Brain Activity via Latent Representation
Yukiyasu Kamitani, Misato Tanaka, Ken Shirakawa
Visual image reconstruction, the decoding of perceptual content from brain activity into images, has advanced significantly with the integration of deep neural networks (DNNs) and…