Takuya Matsuyama — accepted AI-conference papers

2026

LaVCa: LLM-assisted Visual Cortex Captioning

Takuya Matsuyama, Shinji Nishimoto, Yu Takagi

ICLR 2026poster

Understanding the properties of neural populations (or voxels) in the human brain can advance our comprehension of human perceptual and cognitive processing capabilities and contribute to developing brain-inspired computer models. Recent encoding models using deep neural networks (DNNs) have success…

Cited by 0 Source ↗code ↗Scholar ↗

2024

Unveiling Multi-level and Multi-modal Semantic Representations in the Human Brain using Large Language Models

Yuko Nakagi, Takuya Matsuyama, Naoko Koide-Majima, Hiroto Q. Yamaguchi, Rieko Kubo, Shinji Nishimoto +1

EMNLP 2024main

In recent studies, researchers have used large language models (LLMs) to explore semantic representations in the brain; however, they have typically assessed different levels of semantic content, such as speech, objects, and stories, separately. In this study, we recorded brain activity using functi…

Cited by 3 Source ↗PDF ↗code ↗Scholar ↗