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Press release of our new paper, with Masafumi Oizumi and Y. Aoki, out in Cerebral Cortex! We identified network cores with strong bidirectional connections in the mouse brain and discussed the relationship between the cores and consciousness. u-tokyo.ac.jp/focus/en/press…

【拡散歓迎】 今年は #ASCONE 復活します！ 脳科学への数理的アプローチや計算神経科学に興味のある方はぜひご応募ください。 開催地は木更津。講師等詳細はスレッドかWebで。 日本神経回路学会 オータムスクール #ASCONE2022 10月13日〆 ascone.brainsci.net

Is my “red” your “red”? In this preprint with Ariel Zeleznikow-Johnston, Nao Tsuchiya, Masafumi Oizumi, we propose a novel quantitative method to compare subjective experiences in a purely unsupervised manner based on the qualia structure paradigm. 1/13 psyarxiv.com/h3pqm/

Finally out in #JNeurosci! We quantified control cost to transition brain states in a stochastic manner. We applied this method to HCP data and identified significant brain regions for controlling state transitions. See more details in my previous thread! jneurosci.org/content/43/2/2…

Press release from the University of Tokyo for our latest paper in #JNeuosci! SK Genji Kawakita Shuntaro Sasai (笹井俊太朗) Jun Kitazono With our control theory framework, we examined the significant brain regions for the optimal control in human fMRI data. u-tokyo.ac.jp/focus/en/press…

New results just added by Annie G. Bryant in an update to arxiv.org/abs/2201.11941, highlighting some high-performing statistics of coupling in EEG and fMRI time series 👀

🚀New Preprint by Shikauchi et al🧠 Our method combines network control theory with perturbation inputs (TMS) to explore brain dynamics (EEG responses). Co-authored with Leo Tomasevic Jun Kitazono Hartwig Roman Siebner Masafumi Oizumi

This work was led by Yumi Shikauchi, a former postdoc in my lab. The TMS-EEG data during motor tasks were collected by Mitsuaki Takemi / 武見 充晃, Leo Tomasevic, and Hartwig Roman Siebner, while Jun Kitazono and I contributed on the theoretical side. Thanks to the team for making this possible!

Our latest preprint is out! How can we design optimal perturbations—such as TMS, tACS, and tDCS—to accurately identify neural dynamics? By designing perturbations based on system’s eigenvalues and network structure, we can improve system identification. biorxiv.org/content/10.110…

Grateful to my co-authors D. Sekizawa and Jun Kitazono, and especially to my supervisor Masafumi Oizumi! This collaboration made our latest study possible.

So happy to see Taguchi-san’s paper published! I had the pleasure of closely guiding this work — it’s been incredibly rewarding to watch it take shape over time. A real testament to his perseverance and dedication — well done! For more details, check out the thread under his

Applications for this (well-paid) postdoctoral position in our group in Sydney, Australia close in a few days. Anyone interested in complex systems and/or neural dynamics 👀👇

Excited to share our new paper in iScience! 🎉 cell.com/iscience/fullt… We present an unsupervised alignment framework applied to neural recordings, enabling comparison of neural representations across individuals and brain areas—without relying on stimulus correspondence.

Excited to share another new paper in Journal of Neuroscience Methods! We introduce GWTune, a toolbox for unsupervised alignment using Gromov–Wasserstein Optimal Transport (GWOT). Open-source and ready to use. 🔗 doi.org/10.1016/j.jneu… 🧰 oizumi-lab.github.io/GWTune/

#JNeurosci: Findings from T.Taguchi Jun Kitazono Shuntaro Sasai (笹井俊太朗) and Masafumi Oizumi offer novel insights into how network cores with strong bidirectional interactions contribute to the mechanisms underlying conscious perception and cognitive functions. vist.ly/3n5nakw