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Neural Systems Engineering Lab (NSELab)
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A lab that studies and modulates nerve function using electrical and magnetic stimulation.
AboutAbout the lab
Measuring and modulating the nervous system
NSELab studies neurotechnology that uses electrical and magnetic signals to stimulate, monitor, and modulate neural activity.
The lab takes an interdisciplinary approach that combines neural engineering, neuroscience, and computational methods.
Its goal is to understand how nerves respond to external stimulation and to build technologies that are effective, precise, and safe.
The lab welcomes third-year students in the Medical Engineering Course, as well as students from other universities who wish to join as research students or enter graduate school.
Key terms
- Neurotechnology
- A group of technologies that stimulate or investigate neural activity using signals such as electrical and magnetic ones
- Neuromodulation
- Changing how the nervous system functions by applying external stimulation
- In silico experiments
- Experiments carried out on computational models on a computer, rather than in a real body
NewsLab news
An undergraduate student received the Best Poster Award at the Biomedical Engineering Symposium 2024
Paper accepted by IEEE Robotics and Automation Letters
Paper accepted by Journal of Clinical Medicine
Paper accepted by Frontiers in Human Neuroscience
Paper accepted by IEEE Robotics and Automation Letters
ResearchResearch themes
The lab develops technologies that change nerve function through electrical and magnetic stimulation, moving back and forth between experiments on computational models and actual measurements.
*Illustrative imageModulating nerves with electrical and magnetic stimulation
Natural stimuli, such as reading, also evoke neural activity and can lead to long-lasting changes. Building on this idea, the lab uses electrical and magnetic stimulation to produce neuromodulation effects. It aims to create solutions for neural impairments and diseases and to better understand the central and peripheral nervous systems.
*Illustrative imageMoving between computational models and measurements
The lab conducts in silico experiments that reproduce, at the level of the individual, the phenomena caused by neural stimulation. The computational models are verified against measurements and refined. This creates a two-way framework in which the models guide experimental design and the data improve the accuracy of the models.
*Illustrative imageMultiscale models down to the cellular level
The lab uses multiscale neural firing models that connect neural circuits in the brain to peripheral nerves to study what neural stimulation does at the cellular level. It aims to control neural activity precisely and to modulate targeted neural pathways.
MembersFaculty
The members of NSELab include faculty, doctoral, master's, and undergraduate students, and research students.As of 2026
- Associate ProfessorJose Gomez-Tames
VoicesStudent voices
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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: “Neuro-ms” Baburov / CC BY-SA 4.0 (cropped)
- Modulating nerves with electrical and magnetic stimulation: “Tens” Yeza / CC BY-SA 4.0 (cropped)
- Moving between computational models and measurements: “Mathematical and Simulation Modeling in Neuroscience (NeuroMat 2018) 03” Sturm / CC BY-SA 4.0 (cropped)
- Multiscale models down to the cellular level: “Layers of nerve cells in the retina” National Institutes of Health (NIH) / Public domain (cropped)
- Related lab ((Symbiosis 1) Bioprocess Chemistry Lab): “Lab-on-a-chip; Micro Microwave ( )” National Institute of Standards and Technology / Public domain (cropped)
- Related lab (Electrical Energy Applications Lab): “Superconductor” Edosz2010 / CC BY 4.0 (cropped)
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- Related lab ((Kyosei 16) Molecular Structure Analysis Chemistry Lab): “Artistic Crystallization, Bottom View” Paolo Infante / CC BY-SA 4.0 (cropped)
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