What makes us adaptive?

The human brain can learn, generalize, and flexibly adjust behavior to meet ever-changing demands. We study the neural and computational mechanisms underlying this capacity—cognitive control.

We study human cognition using behavioral experiments, EEG, fMRI, transcranial ultrasound stimulation (TUS), and computational modeling.

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2026-06 (upcoming) – Atsushi gives an invited talk for the Cognitive Psychology Colloquium at Leiden University.
2026-04 – 🏅 Honorable Mention Award at CHI 2026 for FIXical I/O (Lee, Vaichalkar, Dadarya, Chang, Kikumoto, & Nishida). Congrats Kyungyeon!
2026–2027 – Atsushi receives the Zimmerman Innovation Award, Carney Institute of Brain Science, for a project on modulating interoceptive circuits to enhance fear regulation in anxiety with TUS (PI: Frederike Petzschner).
2025-09 – Atsushi presents at the Carney Center for Computational Brain Science, Brown University.
2025-02 – Atsushi gives an invited talk for the BrainMap Seminar Series at the Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital.
2025-02 – Atsushi presents for the Wang Lab at New York University.
2024-06 – Atsushi presents for the Woolgar Lab at the University of Cambridge.
2024-03 – Atsushi gives an invited talk for the Cognitive Control Collaborative at the University of Iowa.
2022 – Atsushi serves as a tutor for the BrainStorm Computational Modeling in EEG Workshop and Datathon at Brown University.
2021-11 – Atsushi presents for the Wouter Lab at the Washington University.
2020-05 – Atsushi presents for the Knight Lab at the University of California, Berkeley.
2021–2026 – Atsushi serves as Co-Investigator on the NIH R01 "The organization of neural representations for flexible behavior in the human brain."
2022–2025 – Atsushi receives the Dean's Faculty Fellowship at Brown University.
2021 – Atsushi receives the JSPS Overseas Fellowship (海外特別研究員).
2018–2019 – Atsushi serves as Co-Investigator on the JSPS KAKENHI Challenging Research (挑戦的研究萌芽), "Assessing iconic memory using EEG time–frequency analysis."