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High-resolution image reconstruction with latent diffusion models from human brain activity

脳活動と画像生成AIについて潜在表現間の定量的関係性を示し、脳活動からの知覚内容の解読(映像化)、AI潜在表現の脳活動からの解釈などを行いました。本論文はScience、Newsweek、朝日新聞等を含む世界各国60以上のメディアで報道されました。

Takagi Y, Nishimoto S

The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023)

Brain networks are decoupled from external stimuli during internal cognition

外界に注意を向けているときと内的思考(空想、暗算等) を行っているときの脳活動の関係性を調べることで、内的思考を行っている際には脳内ネットワークにおける情報の分離が起こることを発見しました。

Cohen D, Nakai T, Nishimoto S.

NeuroImage (2022)

Distinct dimensions of emotion in the human brain and their representation on the cortical surface

多様な情動についての脳機能を調べるため、感情を喚起する視聴覚刺激(動画)を見ている際の脳活動を80種類の情動特徴を用いてモデル化し、情動の脳内意味空間の定量やその機能構造の可視化を行いました。

Koide-Majima N, Nakai T, Nishimoto S

NeuroImage (2020)

Quantitative models reveal the organization of diverse cognitive functions in the brain

認知的な脳機能全般を司る脳内認知表現を定量するため、103種類の認知課題遂行中の脳活動を認知特徴を用いてモデル化し、認知表現空間やその機能構造の定量を行いました。本論文はNature Communications誌編集部の選ぶEditor’s Highlightsに選出されました。

Nakai T, Nishimoto S

Nature Communications (2020)

 

論文 (2020年以降)

Mental image reconstruction from human brain activity: Neural decoding of mental imagery via deep neural network-based Bayesian estimation
Koide-Majima N, Nishimoto S, Majima K
Neural Networks (2024)

Inserting a Neuropixels probe into awake monkey cortex: two probes, two methods
Namima T, Kempkes E, Smith B, Smith L, Orsborn AL, Pasupathy A
Journal of Neuroscience Methods (2023)

Artificial neural network modelling of the neural population code underlying mathematical operations
Nakai T, Nishimoto S
NeuroImage (2023)

High-resolution image reconstruction with latent diffusion models from human brain activity
Takagi Y, Nishimoto S
The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023)

Quantitative modelling demonstrates format-invariant representations of mathematical problems in the brain
Nakai T, Nishimoto S
European Journal of Neuroscience (2023)

Disorganization of Semantic Brain Networks in Schizophrenia Revealed by fMRI
Matsumoto Y, Nishida S, Hayashi R, Son S, Murakami A, Yoshikawa N, Ito H, Oishi N, Masuda N, Murai T, Friston K, Nishimoto S, Takahashi H
Schizophrenia Bulletin (2023)

Representations and decodability of diverse cognitive functions are preserved across the human cortex, cerebellum, and subcortex
Nakai T, Nishimoto S
Communications Biology (2022)

What can we experience and report on a rapidly presented image? Intersubjective measures of specificity of freely reported contents of consciousness
Chuyin Z, Koh ZH, Gallagher R, Nishimoto S, Tsuchiya N
F1000Research (2022)

Brain networks are decoupled from external stimuli during internal cognition
Cohen D, Nakai T, Nishimoto S.
NeuroImage (2022)

Voluntary control of semantic neural representations by imagery with conflicting visual stimulation
Fukuma R, Yanagisawa T, Nishimoto S, Sugano H, Tamura K, Yamamoto S, Iimura Y, Fujita Y, Oshino S, Tani N, Koide-Majima N, Kamitani Y, Kishima H.
Communications Biology (2022)

Processing of visual statistics of naturalistic videos in macaque visual areas V1 and V4
Hatanaka G, Inagaki M, Takeuchi RF, Nishimoto S, Ikezoe K, Fujita I
Brain Structure and Function (2022)

Music genre neuroimaging dataset
Nakai T, Koide-Majima N, Nishimoto S
Data in Brief (2022)

Multiple states in ongoing neural activity in the rat visual cortex
Konno D, Nishimoto S, Suzuki T, Ikegaya Y, Matsumoto N
PLoS One (2021)

Reduction of Information Collection Cost for Inferring Brain Model Relations From Profile Information Using Machine Learning
Shinkuma R, Nishida S, Maeda N, Kado M, Nishimoto S
IEEE Transactions on Systems, Man, and Cybernetics: Systems (2021)

Behavioral correlates of cortical semantic representations modeled by word vectors
Nishida S, Blanc A, Maeda N, Kado M, Nishimoto S
PLoS Computational Biology (2021)

Convergence of Modality Invariance and Attention Selectivity in the Cortical Semantic Circuit
Nakai T, Yamaguchi HQ, Nishimoto S
Cerebral Cortex (2021)

Expert Programmers Have Fine-Tuned Cortical Representations of Source Code
Ikutani Y, Kubo T, Nishida S, Hata H, Matsumoto K, Ikeda K, Nishimoto S
eNeuro (2021)

Correspondence of categorical and feature-based representations of music in the human brain
Nakai T, Koide-Majima N, Nishimoto S
Brain and Behavior (2021)

Distinct dimensions of emotion in the human brain and their representation on the cortical surface
Koide-Majima N, Nakai T, Nishimoto S
NeuroImage (2020)

Brain-Mediated Transfer Learning of Convolutional Neural Networks
Nishida S, Nakano Y, Blanc A, Maeda N, Kado M, Nishimoto S
Proceedings of the AAAI Conference on Artificial Intelligence (2020)

Quantitative models reveal the organization of diverse cognitive functions in the brain
Nakai T, Nishimoto S
Nature Communications (2020)

(より詳細なリストはGoogle ScholarResearchMapなどをご参照ください)