Gouki Okazawa 岡澤 剛起
I am a systems neuroscientist studying the computational mechanisms of cognitive functions in primates.
My lab combines population neural recordings in macaque monkeys, computational modeling, and perturbation methods
to understand the fundamental cognitive algorithms of the brain.
okazawa@ion.ac.cn
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Research Overview
Our lab aims to develop interpretable models of fundamental cognitive functions in primates — models that can
explain the basic computational elements needed for real-world behavior. We study how the brain
recognizes objects, makes decisions, and adapts its behavior to context,
using a combination of neural population recordings in macaques, computational modeling, and perturbation methods.
We approach cortical computation using the language of population geometry and dynamical systems.
See the Research page for details on our current directions.
Recent Highlights
The 'neat' and 'messy' in task-dependent neural geometry and computation
Xue C, Okazawa G — Trends in Neurosciences 49:522–535 (2026)
Discussed task-dependent neural computations, including both structured neural representations ("neat") and complex behavioral and neural features that defy normative theories ("messy").
A battery of image classification challenges reveals shared and distinct object categorization behavior across monkeys, humans, and deep networks
Zhang H, Zheng Z, Hu J, Wang Q, Xu M, Zhou Z, Li Z, Okazawa G — eLife 111725.1 (2026)
Macaque monkeys rapidly learn to classify natural images across 10+ binary rules (animate/inanimate, natural/man-made, mammal/non-mammal, etc.), generalize to new images, and correlate more strongly with language-free DNNs than language-informed ones.
Inferotemporal cortex encodes formation and termination of perceptual decisions
Okazawa G, Kiani R (2025) — bioRxiv
How does the visual cortex contribute to decision making? We recorded from IT cortex during a face categorization task and found signals reflecting ongoing decision formation and termination.
Limitation of switching sensory information flow in flexible perceptual decision making
Luo T, Xu M, Zheng Z, Okazawa G (2025) — Nature Communications
We identified a brief reduction in sensory processing efficiency immediately after switching a task rule, pinpointing a computational bottleneck in flexible decision circuits.