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Perceptual and Cognitive Neuroscience Laboratory

Prof. NISHIMOTO Shinji Prof. NISHIMOTO Shinji

Keywords：

Natural perception, Cognition, Brain Representation, Systems Neuroscience

Quantitative understanding of the human brain

We aim to understand the neural basis underlying diverse perceptual and cognitive functions in the human brain. More specifically, our research focuses on understanding neural processing and representation by building predictive models of brain activity evoked under natural perceptual and cognitive conditions. Using such models, we also aim to develop quantitative bases for decoding brain activity as a medium for communications.

Schematics of our approach. We record brain activity evoked by natural perceptual and cognitive experiences and build predictive models. By analyzing the models, we aim at understanding information processing and representation in the brain.

Members

Shinji Nishimoto (Professor) nishimoto.shinji.fbs[at]osaka-u.ac.jp
Tomoyuki Namima (Assistant Professor) namima.fbs[at]osaka-u.ac.jp
Masahiro Yamashita (Researcher)  
Naoto Ichikawa (Technical Staff)  
Akiko Yamamoto (Technical Staff)  

You could probably reach more information of individual researchers by Research Map and researcher's search of Osaka-U.

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Q＆A

What is your hot research topic?
Recent development in machine learning techniques, including deep learning and natural language processing, allow us to build more accurate predictive models of brain activity. Using such technologies, we aim to acquire new quantitative knowledge and interpretations on information processing and representation in the brain.
What kind of background do your lab members have？
Our research members (FBS/NICT) have diverse backgrounds, including biophysics, neurophysiology, computer science, psychology, and art.
Do you collaborate with other institutions and universities?
We are collaborating with NICT CiNet (close relation with Osaka University CiNet), University of Tokyo (JST ERATO/Mirai Program), and other research institutes.

Research Highlights

Publications (Research Articles, Reviews, Books)

2024

Namima T, Kempkes E, Zamarashkina P, Owen N, Pasupathy A

High-density recording reveals sparse clusters (but not columns) for shape and texture encoding in macaque V4

Journal of Neuroscience 45:e1893232024  2024 （PMID：39562041 DOI：10.1523/JNEUROSCI.1893-23.2024）

Nakagi Y, Matsuyama T, Koide-Majima N, Yamaguchi HQ, Kubo R, Nishimoto S, Takagi Y

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

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP) 20313-20338  2024 （ DOI：10.18653/v1/2024.emnlp-main.1133）

Hayashi R, Kaji S, Matsumoto Y, Nishida S, Nishimoto S, Takahashi H

Homogenization of word relationships in schizophrenia: Topological analysis of cortical semantic representations

Psychiatry and Clinical Neurosciences 78(11):687-695  2024 （PMID：39194166 DOI：10.1111/pcn.13727）

Ikegawa Y, Fukuma R, Sugano H, Oshino S, Tani N, Tamura K, Iimura Y, Suzuki H, Yamamoto S, Fujita Y, Nishimoto S, Kishima H, Yanagisawa T

Text and image generation from intracranial electroencephalography using an embedding space for text and images

Journal of Neural Engineering 21:036019  2024 （PMID：38648781 DOI：10.1088/1741-2552/ad417a）

Okumura T, Kida I, Yokoi A, Nakai T, Nishimoto S, Touhara K, Okamoto M

Semantic context-dependent neural representations of odors in the human piriform cortex revealed by 7T MRI

Human Brain Mapping 45:e26681  2024 （PMID：38656060 DOI：10.1002/hbm.26681）

Koide-Majima N, Nishimoto S, Majima K

Mental image reconstruction from human brain activity: Neural decoding of mental imagery via deep neural network-based Bayesian estimation

Neural Networks 170:349-363  2024 （PMID：38016230 DOI：10.1016/j.neunet.2023.11.024）

2023

Namima T, Kempkes E, Smith B, Smith L, Orsborn AL, Pasupathy A

Inserting a Neuropixels probe into awake monkey cortex: two probes, two methods

Journal of Neuroscience Methods 402:110016  2023 （PMID：37995854 DOI：10.1016/j.jneumeth.2023.110016）

Nakai T, Nishimoto S.

Artificial neural network modelling of the neural population code underlying mathematical operations

NeuroImage 270:119980  2023 （PMID：36848969 DOI：10.1016/j.neuroimage.2023.119980）

Takagi Y, Nishimoto S.

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

The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2023:14453-14463  2023 （ DOI：10.1109/CVPR52729.2023.01389）

Nakai T, Nishimoto S.

Quantitative modelling demonstrates format-invariant representations of mathematical problems in the brain

European Journal of Neuroscience 57(6):1003-1017  2023 （PMID：36710081 DOI：10.1111/ejn.15925）

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.

Disorganization of Semantic Brain Networks in Schizophrenia Revealed by fMRI

Schizophrenia Bulletin sbac157  2023 （PMID：36542452 DOI：10.1093/schbul/sbac157）

2022

Nakai T, Nishimoto S.

Representations and decodability of diverse cognitive functions are preserved across the human cortex, cerebellum, and subcortex

Communications Biology 5(1):1245  2022 （PMID：36376490 DOI：10.1038/s42003-022-04221-y）

Chuyin Z, Koh ZH, Gallagher R, Nishimoto S, Tsuchiya N.

What can we experience and report on a rapidly presented image? Intersubjective measures of specificity of freely reported contents of consciousness

F1000Research 11:69  2022 （PMID：36176545 DOI：10.12688/f1000research.75364.2）

Klein-Flugge MC, Jensen DEA, Takagi Y, Priestley L, Verhagen L, Smith SM, Rushworth MFS.

Relationship between nuclei-specific amygdala connectivity and mental health dimensions in humans

Nature Human Behaviour   2022 （PMID：36138220 DOI：10.1038/s41562-022-01434-3）

Cohen D, Nakai T, Nishimoto S.

Brain networks are decoupled from external stimuli during internal cognition

Neuroimage 256:119230  2022 （PMID：35460919 DOI：10.1016/j.neuroimage.2022.119230）

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.

Voluntary control of semantic neural representations by imagery with conflicting visual stimulation

Communications Biology 5(1):214  2022 （PMID：35304588 DOI：10.1038/s42003-022-03137-x）

Hatanaka G, Inagaki M, Takeuchi RF, Nishimoto S, Ikezoe K, Fujita I.

Processing of visual statistics of naturalistic videos in macaque visual areas V1 and V4

Brain Structure and Function 227(4):1385-1403  2022 （PMID：35286478 DOI：10.1007/s00429-022-02468-z）

Nakai T, Koide-Majima N, Nishimoto S.

Music genre neuroimaging dataset

Data in Brief 40:107675  2022 （PMID：34917714 DOI：10.1016/j.dib.2021.107675）

2021

Konno D, Nishimoto S, Suzuki T, Ikegaya Y, Matsumoto N.

Multiple states in ongoing neural activity in the rat visual cortex.

PLoS One 16(8):e0256791  2021 （PMID：34437630 DOI：10.1371/journal.pone.0256791）

Shinkuma R, Nishida S, Maeda N, Kado M, Nishimoto S.

Reduction of Information Collection Cost for Inferring Brain Model Relations From Profile Information Using Machine Learning

IEEE Transactions on Systems, Man, and Cybernetics: Systems   2021 （ DOI：10.1109/TSMC.2021.3074069）

Nishida S, Blanc A, Maeda N, Kado M, Nishimoto S.

Behavioral correlates of cortical semantic representations modeled by word vectors.

PLoS Computational Biology 17(6):e1009138  2021 （PMID：34161315 DOI：10.1371/journal.pcbi.1009138）

Nakai T, Yamaguchi HQ, Nishimoto S.

Convergence of Modality Invariance and Attention Selectivity in the Cortical Semantic Circuit.

Cerebral Cortex bhab125  2021 （PMID：33999141 DOI：10.1093/cercor/bhab125）

Ikutani Y, Kubo T, Nishida S, Hata H, Matsumoto K, Ikeda K, Nishimoto S.

Expert Programmers Have Fine-Tuned Cortical Representations of Source Code.

eNeuro 8(1):ENEURO.0405-20.2020  2021 （PMID：33318072 DOI：10.1523/ENEURO.0405-20.2020）

Nakai T, Koide-Majima N, Nishimoto S.

Correspondence of categorical and feature-based representations of music in the human brain.

Brain and Behavior 11(1):e01936  2021 （PMID：33164348 DOI：10.1002/brb3.1936）

2020

Koide-Majima N, Nakai T, Nishimoto S.

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

Neuroimage 222:117258  2020 （PMID：32798681 DOI：10.1016/j.neuroimage.2020.117258）

Nishida S, Nakano Y, Blanc A, Maeda N, Kado M, Nishimoto S.

Brain-Mediated Transfer Learning of Convolutional Neural Networks.

Proceedings of the AAAI Conference on Artificial Intelligence 34:5281-5288  2020 （ DOI：10.1609/aaai.v34i04.5974）

Nakai T, Nishimoto S.

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

Nature Communications 11(1):1142  2020 （PMID：32123178 DOI：10.1038/s41467-020-14913-w）

Our ideal candidate (as a graduate student)

We are looking for a highly motivated person to work on our research topics as our lab members.

Contact

Perceptual and Cognitive Neuroscience Laboratory, Graduate School of Frontier Biosciences, Osaka University,
1-4 Yamadaoka, Suita, Osaka 565-0871 Japan.
E-mail: nishimoto.shinji.fbs[at]osaka-u.ac.jp (Prof. NISHIMOTO Shinji)

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