4 papers
Phantom Evidence: How and Why Generative AI Manufactures False Positives in Science
Yukiyasu Kamitani, Ken Shirakawa
Four centuries ago Francis Bacon warned against the anticipations of nature, hasty generalization that wins assent on a few facts, and set against it the table of absence: checking…
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…
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…
Spurious reconstruction from brain activity
Ken Shirakawa, Yoshihiro Nagano, Misato Tanaka +4
Advances in brain decoding, particularly visual image reconstruction, have sparked discussions about the societal implications and ethical considerations of neurotechnology. As the…