日本語JA

ResearchOverview

This page provides an overview of the research conducted in the laboratory. Through its major research pillars, representative projects, and methodological approaches, it introduces the breadth of themes explored in the laboratory.

Overall Research Vision

At the laboratory, we investigate how sensory inputs (vision, olfaction, thermal perception, etc.) relate to higher-order functions such as cognition and motivation. Our work aims not only to clarify mechanisms of information processing in the human brain, but also to explore approaches for enhancing motivation and creative thinking. In recent years, we have integrated Field Neuroscience—physiological measurements conducted in real-world environments—with approaches that introduce a future-oriented perspective into present decision-making through Future Design.

This page introduces the main pillars of our research and representative examples. For a more conceptual framework, please see Future Brain Science.

From Sensation to Higher Cognition: Connecting to Thinking and Motivation

We are interested in how sensory inputs affect emotion and cognition, and how these influences extend to the quality of thinking and intrinsic motivation. While sensory processing provides a tractable entry point, connecting it to higher-order cognition requires careful experimental design, analysis, and modeling.

In olfactory research, we have led an interdisciplinary project spanning molecular biology, behavior, and brain activity, coordinating researchers across agriculture, medicine, science, engineering, and the humanities.

Representative examples include:

  • Physiological and computational studies of orientation selectivity in the primary visual cortex of macaques
  • EEG studies on the effects of odor stimuli on working memory and emotion
  • Research on olfaction in relation to circadian rhythms and sleep-related olfactory gating

Field Neuroscience: Measuring Brain Activity in Real-World Contexts

In addition to controlled laboratory experiments, we conduct physiological measurements in environments close to real-life settings. We examine how thermal conditions, spatial materials, odors, and even outdoor bonfire experiences influence thinking and emotion.

Representative studies include:

  • Evaluation of thermal comfort and its physiological correlates
  • Effects of wooden materials on psychological and physiological responses in living spaces
  • Integrated EEG analysis in outdoor bonfire environments (summarized in the book Neuroscience of Bonfires)

In collaborative projects with companies and public institutions, we design evaluation indices and explore pathways toward real-world application.

Neurofeedback: Interventions for Modulating Brain Function

Beyond measuring brain activity, we develop neurofeedback-based interventions aimed at actively enhancing brain function. This framework allows us to move back and forth between understanding mechanisms and developing methods to enhance them.

  • Development of real-time EEG-based neurofeedback techniques
  • Empirical studies demonstrating memory enhancement after three-day training
  • Applied practice in elite sports settings (Japanese national men’s tennis training camp)

Introducing a Future Standpoint through Future Design

Future Design is a framework that adopts the standpoint of the future in order to reconsider present decision-making and institutional design. We examine how such perspective shifts influence the quality of thinking and intrinsic motivation from a neuroscientific viewpoint.

  • Presentations at the Future Design Society
  • Practical studies using plastic waste issues as case examples
  • Educational initiatives in collaboration with governmental institutions and research organizations

Our focus is not merely on decision outcomes, but on the processes through which deeper thinking and intrinsic motivation emerge when future benefits are incorporated into present choices.

Methodological Approaches

  • Measurement of EEG, ECG, and other physiological signals (laboratory and field settings)
  • Event-related potential (ERP) analysis
  • Statistical modeling, machine learning, and causal inference
  • Real-time signal processing for intervention design
  • Neuroimaging analysis, phase synchronization analysis, and Bayesian network-based causal structure modeling

For Students and Collaborators

Research themes and approaches evolve flexibly according to students’ interests and the development of collaborative projects. We welcome those who are willing to engage in experiments, data analysis, and theoretical exploration.

We also welcome collaborations with researchers, companies, and public institutions. If you are interested, please contact us via Contact.

First published: August 13, 2014.
Major revision: February 18, 2026.
Last updated: April 15, 2026.