Brain–computer interface (BCI) research has achieved remarkable technical progress but remains limited in scope, typically relying on motor
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@kamitani-lab
Brain–computer interface (BCI) research has achieved remarkable technical progress but remains limited in scope, typically relying on motor

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(人工知能学会誌『人工知能』掲載予定の原稿を一部改訂したものです。編集部の許可を得て掲載しています。内容は2023年の日本心理学会シンポジウムでの発表をベースにしています[スライド]) はじめに 「脳とAIは似ているか」という古くからある問いは、近年のAIの急速な進展によっ
A recent high-profile study by Koide-Majima et al. (2024) claimed a major advance in reconstructing visual imagery from brain activity using
ヒューマニエンス 40億年のたくらみのリリース情報や番組からのお知らせなど、最新の情報をお届けします。「ヒューマン」と「サイエンス」の造語「ヒューマニエンス」。人間という不確かで不思議な存在とはいったい何なのか?その真の姿に迫っていくシリーズ。番組MCは、織田裕二さん、NHKアナ
「ヒューマニエンス40億年のたくらみ “睡眠”ヒトは眠りで進化した?」の再放送 11月6日(木)午前10時から NHK-BS

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Sensory representation is typically understood through a hierarchical-causal framework where progressively abstract features are extracted s
Critical evaluation of "mental image reconstruction": Commentary on Koide-Majima, Nishimoto, and Majima (2024)
日本神経回路学会ポスター
Advances in brain-to-image reconstruction are enabling us to externalize the subjective visual experiences encoded in the brain as images. A
Otsuka et al., arxiv 2025
Visual image reconstruction, the decoding of perceptual content from brain activity into images, has advanced significantly with the integra
社会課題と向き合う科学技術の最前線
ATRオープンハウス2025 https://atr.jp/expo/?nl=81 ◆2025年10月2日(木)・3日(金)10:00~17:00 ◆場所:ATR(京都府相楽郡精華町光台2-2-2) ◆内容:展示約60件、講演5件(ライブ配信あり) 私も講演します

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日本神経科学学会50周年記念イベント(2025.8.17) 「 NeuroArt 50: 脳が生む創造性 ― バイオ・AI・美学の交差点」 の趣旨説明のスライド https://www.jnss.org/50th_memorial_year 講演者 - 石津 智
日本神経科学学会50周年記念イベント(2025.8.17) 「 NeuroArt 50: 脳が生む創造性 ― バイオ・AI・美学の交差点」 の趣旨説明のスライド https://www.jnss.org/50th_memorial_year
講演者 - 石津 智大(関西大学) - 高橋洋介(キュレーター/先端領域ELSI研究所「分子ロボット倫理研究会」委員) - 岸 裕真(アーティスト)
モデレータ - 神谷之康(京都大学・ATR)
京都大学 経営管理大学院に開講した「キュレーション理論・実践とマネジメント寄附講座」のキックオフイベントとして、キュレーションの本質や社会的役割を考えるシンポジウムを開催します。... powered by Peatix : More than a ticket.
https://www.nytimes.com/2025/06/10/arts/design/pierre-huyghe-goodman-gallery-ai-art-video.html

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Reconstructing sounds from fMRI data has been challenging due to its limited temporal resolution. This study develops method based on a deep
A neural code conversion method is introduced using deep neural network representations to align brain data across individuals without share