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Mathematical Modeling and Adaptive Networks Lab
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The lab studies the behavior and intelligence of living things using mathematical models.
AboutAbout the lab
Reading the behavior of living things through equations.
The Mathematical Modeling and Adaptive Networks Lab studies the behavior and intelligence of living things using mathematical models.
The lab describes the behavior of single-celled organisms such as true slime molds with equations and reproduces it on a computer to explore the origins of intelligence.
Another research theme is how behavior is controlled, approached through the relationship between periodic movements such as walking and the body's internal state.
The lab is part of the Applied Theory Division at the Institute of Mathematics for Industry.
Key terms
- True slime mold
- An organism made of a single cell containing many nuclei. In its plasmodium state, it shows abilities such as solving mazes.
- Mathematical model
- A method of expressing the behavior of living things and similar phenomena with equations, and studying them by reproducing them on a computer.
NewsLab news
A student won the Best Poster Award at the Cross-Disciplinary and Cross-Industry Research Exchange Meeting 2025
A student won the Best Poster Award at the Cross-Disciplinary and Cross-Industry Research Exchange Meeting 2024
ResearchResearch themes
The lab aims to understand the mechanisms of the behavior of living things using mathematical models. The researcher information page lists the behavior of true slime molds and behavioral control arising from periodic movements as research themes, with a stated research period of 2007 to 2013.
*Illustrative imagePeriodic Movements and Behavioral Control
The lab's view is that periodic movements such as walking affect the body's internal state, reveal rhythms hidden inside the body, and are involved in behavioral control. Focusing on the resonance between periodic movements and the internal state, the lab seeks to understand how living things carry out tasks, using numerical experiments and hardware experiments.
*Illustrative imageThe Origins of Intelligence, Learned from Slime Molds
Experiments have shown that the plasmodium of the true slime mold can solve mazes, find optimal networks, and memorize time intervals to act in anticipation. The lab expresses this behavior with model equations and reproduces it on a computer to investigate the origins of intelligence in living things.
MembersFaculty
- Associate ProfessorAtsushi Tero
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Ethology diversity” DrChrissy / CC BY-SA 3.0 (cropped)
- Periodic Movements and Behavioral Control: “Killer whale echolocation” Uko Gorter / Public domain (cropped)
- The Origins of Intelligence, Learned from Slime Molds: “Maze - Australian physarum polycephalum (cropped)” Tim Tim (VD fr) / CC BY-SA 4.0 (cropped)
- Related lab (Mathematical Modeling and Adaptive Networks Lab): “Unidentified slime mold” Jerzy Opioła / CC BY-SA 4.0 (cropped)
- Related lab (Discrete Differential Geometry and Integrable Systems Lab): “Amper's Geometric Shape Art Project” Neirenz / CC BY-SA 4.0 (cropped)
- Related lab (Numerical Analysis and Computational Fluid Dynamics Lab): “Biomechanics-Femur-Fracture-Nail-Internal Fixation-CAD-FEM” Fry72 Karel Frydrýšek, Tomáš Halo, Daniel Čepica / CC BY-SA 4.0 (cropped)
- Related lab (Numerical Analysis and Computational Fluid Dynamics Lab): “AbsoluteErrorNumericalDifferentiationExample” Berland / Public domain (cropped)
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