The predictive coding theory proposes that the brain continuously generates and updates predictions of sensory information at multiple levels of abstraction, and emits prediction-error signals when the predicted and actual sensory inputs differ. This theory offers a comprehensive framework for understanding perception, action, and internal processes such as creativity. The current focus of my lab’s research includes:

 

• Predictive Coding Circuits　
  Our goal is to unravel the complex networks of microcircuits and macrocircuits essential to predictive coding across different hierarchical levels and sensory domains. Our research spans multiple species—from rodents and marmosets to humans—and combines experimental results from these varied subjects with computational modeling to develop comprehensive insights.

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• Neural Markers for Prediction-Related Psychiatric Disorders　
  A key focus of our research is to identify mechanistic neural markers associated with psychiatric disorders characterized by prediction anomalies, such as autism spectrum disorder. Understanding these neural foundations is essential for comprehending the conditions and could lead to high-resolution diagnoses and targeted interventions.

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• Predictive Coding in Creativity
  We also explore the role of predictive coding in creativity potential, which we define as the brain’s capacity to generate novel and useful ideas for upcoming tasks. Our goal is to provide mechanistic insights into this complex process, linking creativity directly to its neural circuit implementation.

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• Creativity Augmentation for Real-World Applications
  One ambition of our research is to develop a closed-loop system that enhances creativity potential in practical, real-world applications. This system has the potential to transform fields that rely on creative problem-solving by providing innovative tools and methodologies to boost innovation.