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Neuromimetic Systems Lab (Kohno Lab)
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The Neuromimetic Systems Lab studies neuromimetic systems, which reproduce the workings of the brain's neurons with electronic circuits.
AboutAbout the lab
Mimicking the nervous system for flexible, autonomous intelligent processing
The Neuromimetic Systems Lab studies "silicon neuronal networks," which are networks of neurons built from electronic circuits.
The lab aims to make these networks a foundational technology for "brain-compatible" computing systems that process information on the same principles as the brain.
The lab takes a cross-disciplinary approach, combining analog and digital electronic circuit design with mathematical models of neurons and neural networks.
Using nonlinear mathematics in its designs, the lab develops ultra-low-power circuits and works to elucidate the principles of information processing in the brain.
Key terms
- Silicon neuronal network
- A network of artificial neurons built from electronic circuits to reproduce the electrical activity of the nervous system
- Nonlinear mathematics
- Mathematics that deals with complex behavior in which input and output are not proportional. It is used to analyze the activity of neurons
- Synapse
- The junction between neurons. Signals are transmitted through it, and learning occurs as the strength of the connection changes
ResearchResearch themes
The lab studies neural networks made of electronic circuits that reproduce the electrical activity of the nervous system, as a foundation for computing systems that process information on the same principles as the brain. Working in both analog and digital, it centers on two areas: designing circuits that are power-efficient and can be integrated at large scale, and developing theory on how neural spikes represent and process information.
*Illustrative imageNeurons built with analog circuits
These are circuits that solve the equations of neuron models by using the physical properties of electronic components, such as integrating current in a capacitor. Using nonlinear mathematics, the lab developed a design method that is robust to transistor variability, and built circuits that reproduce representative types of neurons at ultra-low power. The lab is also working on integrating synapse circuits and related components.
*Illustrative imageNeural networks built with digital circuits
On a single FPGA (field-programmable gate array), a rewritable digital circuit chip, the lab has built a platform that can handle multiple types of neurons and synapses. It uses this platform to build and analyze networks for associative memory and spatiotemporal pattern recognition, and also to elucidate the principles of information processing in local circuits of the brain.
MembersFaculty
The Neuromimetic Systems Lab consists of faculty members, technical specialists and technical assistants, and PhD and master's students.As of 2026
- ProfessorTakashi KohnoPublications ↗
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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: “Cultured Rat Hippocampal Neuron ( )” ZEISS Microscopy from Germany / CC BY 2.0 (cropped)
- Neurons built with analog circuits: “AD574 Analog-Digital Converter Dieshot” Lhfjames / CC BY-SA 4.0 (cropped)
- Neural networks built with digital circuits: “Neurons (Purkinje cells)” Lennart Rikk / CC0 (cropped)
- Related lab (Takenaka Lab): “Silicon Photonics 300mm wafer” Ehsanshahoseini / CC BY-SA 4.0 (cropped)
- Related lab (Yamashita-Set Lab): “Зеркало резонатора волоконного лазера в темноте (Resonator mirror of Er ZBLAN fiber laser and its working fiber in the dark)” Hius1 / CC BY 4.0 (cropped)
- Related lab (Toprasertpong Lab): “Ferroelectric domains at a PZT grain boundary ( )” Oak Ridge National Laboratory / CC BY 2.0 (cropped)
- Related lab (Tabata-Matsui-Seki Lab): “Pulsed Laser Deposition in Action” Adam Andersen Læssøe / CC BY-SA 4.0 (cropped)
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