🔬 Research

I aim to understand animal behavior from molecular mechanisms to evolutionary processes, and to explore how behavioral diversity shapes social dynamics and ecosystems. My research has involved a variety of organisms—including humans, rabbits, mice, flies, and crustaceans—using a broad range of experimental and analytical approaches. Looking ahead, I hope to expand this work beyond basic science, applying it to fields such as mental health and marine conservation. With an open and creative mindset, I am committed to pursuing science that bridges disciplines and fosters innovation.

My main research themes to date are as follows:

Evolutionary and genetic bases of human psychological diversity

Understanding the genetic and evolutionary underpinnings of individual variation in psychological traits—including susceptibility to psychiatric disorders—is a central challenge in psychiatry, neuroscience, and evolutionary genetics. Using approaches from comparative genomics and population genetics, I have shown that a nonsynonymous variant (Thr136Ile) in the vesicular monoamine transporter gene VMAT1, which is associated with several psychiatric conditions, may have been positively maintained during human evolution (Sato & Kawata, 2018 Evolution Letters ). Through ancestral protein reconstruction and functional assays, I further demonstrated that evolutionary changes in VMAT1 reduced monoamine uptake, suggesting that early human evolution may have involved selection pressures favouring increased anxiety (Sato et al., 2019 BMC Evolutionary Biology ). More recently, by generating Vmat1 humanised knock-in mice, I found that Vmat1 genotype alters gene expression and neural activity in the amygdala, ultimately affecting anxiety-like behavior (Sato et al., 2022 iScience ). I am currently extending this work by analysing large-scale cohort data to investigate how such genetic variants shape brain function and personality traits, as well as to better understand the evolutionary mechanisms that maintain this diversity.

Collective effects of behavioral diversity and its “meta-genetic” basis

In recent years, the value of diversity has been increasingly recognised across various social and biological systems. The interplay between individual agency and social interaction can give rise to collective intelligence, enabling groups to achieve outcomes that exceed the capacity of any individual member. I investigate the mechanisms underlying such emergent phenomena using Drosophila melanogaster as a model system. Through large-scale collective behavior experiments combined with genomic analysis, I have demonstrated that behavioral diversity among individuals can influence group performance in a non-additive manner (Okuyama, Sato, and Takahashi, Journal of Experimental Biology ). Additionally, I showed that diversity in fear responses within a group can enhance collective antipredator behavior through synchronised reactions (Sato & Takahashi, in press ). Building on this work, I proposed a new framework for genomic analysis—Genome-wide Higher-level Association Study (GHAS)—which allows for the identification of genetic variants that contribute to enhanced group-level outcomes (i.e., diversity effects) arising from inter-individual interactions.

Transformative insights from large-scale behavioral datasets

As part of my commitment to open science, I strive to share data generated during the research process in formats that facilitate reuse and secondary analysis. For example, I have publicly released a large-scale behavioral dataset comprising over 30,000 individual Drosophila and nearly 10,000 associated video and tracking files, collected under diverse genetic, sex, and social conditions (Sato et al., 2025 Scientific Data ). This dataset represents one of the most comprehensive resources in behavioral genetics and holds great potential for a wide range of research applications. In parallel, I have contributed to the development of a large-scale behavioral database of more than 150 strains of mouse models for psychiatric disorders. Through meta-analyses of this dataset, I am working to establish novel behavioral metrics that better capture phenotypic variation across genotypes (Sato et al., in prep. ).

Observing “real” animal behavior through engineering-based approaches

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How “real” is the behavior we observe in laboratory animals? The presence of human observers, the spatial constraints of artificial arenas, and the absence of natural social and environmental interactions all contribute to conditions that differ significantly from those in the wild. Conversely, the more we attempt to replicate natural conditions in the lab, the more variability (or “noise”) we introduce, making it increasingly difficult to rigorously test specific hypotheses. To address this, I apply approaches such as animal-computer interaction, where stimuli are dynamically presented in response to the animal’s behavior. This enables us to evoke more naturalistic responses. One example involves controlling the movement of virtual flies displayed on a screen to quantify predatory attacks by spiders (Sato & Takahashi, in press). I also use inverse reinforcement learning to infer the underlying reward structures that drive behavior (Sato et al., in prep. ). By integrating such engineering-driven approaches, I aim to advance our understanding of animal decision-making and behavior in more ecologically meaningful contexts.

Genetic basis of tameness and behavioral evolution during domestication

Domestication of animals and cultivation of plants are often regarded as early human-driven evolutionary experiments. In animals, domestication has led to a suite of common changes across species—including alterations in coat colour, skeletal structure, reproductive traits, and especially behavior such as increased tameness—collectively referred to as the “domestication syndrome.” Uncovering the genetic underpinnings of these changes remains a major question in evolutionary biology. Focusing on rabbits, a species famously noted for its docility in The Origin of Species, I investigated changes in brain gene expression associated with domestication. By comparing the brain transcriptomes of domestic and wild rabbits, I identified domestication-related alterations in gene expression patterns (Sato et al., 2020 Genome Biology and Evolution ). Notably, in the amygdala—a brain region involved in emotional regulation—genes related to dopamine signalling showed increased expression in domestic rabbits, suggesting a potential link to enhanced tameness and reduced fear towards humans.

Understanding rapid environmental adaptation in the Anthropocene

Since their emergence, humans have dramatically transformed natural environments through their exceptional cognitive abilities, expanding their habitats across the globe. This unprecedented influence has not only led to declines in the abundance and distribution of many species but has also driven rapid adaptations to novel environments. I have explored these processes by focusing on the invasive red swamp crayfish (Procambarus clarkii), a species that has expanded its range globally and now exerts substantial impacts on native ecosystems. My research revealed that extensive gene duplication and changes in gene regulation in this species may have facilitated adaptation to colder climates (Sato et al., 2023 iScience ). In parallel, I am investigating the effects of artificial light at night (ALAN) on coastal isopods, examining how ALAN alters their behavior, morphology, and habitat use (Sato, submitted). Through a combination of field surveys, behavioral experiments, and genomic and transcriptomic analyses, I aim to uncover how human activities are driving rapid evolutionary responses in wildlife.