2026-05-18 理化学研究所
本研究成果の概要
＜関連情報＞
- https://www.riken.jp/press/2026/20260518_2/index.html
- https://www.nature.com/articles/s41467-026-72918-3
視覚野における注意抑制効果の低下により、タスクとは無関係な自然シーンにおいて教師なし視覚学習が明らかになる Unsupervised visual learning is revealed for task-irrelevant natural scenes due to reduced attentional suppression effects in visual areas
Takeo Watanabe,Yuka Sasaki,Takuro Zama,Julian R. Matthews,Daiki Ogawa & Kazuhisa Shibata
Nature Communications Published:18 May 2026
DOI:https://doi.org/10.1038/s41467-026-72918-3
Abstract
Unsupervised learning—learning through repeated exposure without instruction or reward—is central to both machine learning and human cognition, including language acquisition and statistical learning. However, its role in visual perceptual learning (VPL) remains debated, as previous studies have not shown VPL for task-irrelevant but visible features, particularly in artificial stimuli. Here, we show that task-irrelevant exposure to natural scene images induces robust VPL, while artificial images that lack complex structure characteristics of natural scene images, known as higher-order statistics, do not. Behavioral and fMRI results suggest that although unsupervised learning underlies VPL, it can be suppressed by top-down attention. Higher-order statistics may evade this suppression, possibly because their slower processing reaches visual areas beyond V1 outside the optimal temporal window for attentional suppression. These findings suggest that unsupervised learning underlies VPL, but its occurrence depends on both higher-order stimulus structure and the brain’s attentional gating mechanisms.
