2 citations · 4 across the 5 of their papers we have counts for
5 papers
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…
Inter-individual and inter-site neural code conversion without shared stimuli
Haibao Wang, Jun Kai Ho, Fan L. Cheng +4
Inter-individual variability in fine-grained functional brain organization poses challenges for scalable data analysis and modeling. Functional alignment techniques can help mitiga…
Sound reconstruction from human brain activity via a generative model with brain-like auditory features
Jong-Yun Park, Mitsuaki Tsukamoto, Misato Tanaka +1
The successful reconstruction of perceptual experiences from human brain activity has provided insights into the neural representations of sensory experiences. However, reconstruct…