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Optimization of electrode selection for HD-MEA based neural signal recording
This project is about the development of integrated circuits to study neurons and neural networks, and focuses on solving the optimization problem to find and interconnect the electrodes that capture the most significant signals in a neural in-vitro culture.
Keywords: Optimization, Microelectrode array, neural recording, microelectronics, data compression
Neural cells can be culture on top of microelectrode arrays (MEAs), what allows stimulating neurons and monitoring their electrical activity. This allows the study of neuronal information processing, mental diseases, and the effects of drugs in electrogenic cells.
High density MEAs can comprise tens of thousands of microelectrodes with a pitch below 20um, what gives subcellular resolution and allows the measurement of each neuron by more than one electrode. However, recording the signals captured by all this electrodes is challenging, and typically only a reduced portion of the electrodes (<10%) can be recorded.
In this project the student will try to solve the different optimization problems that arise during the design of a MEA, such as the selection of the best recording electrodes and the interconnection of these electrodes to the on-chip analog-to-digital converters. The project can also include a section about neural signal compression, depending on the interests and background of the student.
Preferred skills:
- Background including mathematical optimization
- MATLAB
- C++ (ideally also Qt Creator)
Neural cells can be culture on top of microelectrode arrays (MEAs), what allows stimulating neurons and monitoring their electrical activity. This allows the study of neuronal information processing, mental diseases, and the effects of drugs in electrogenic cells.
High density MEAs can comprise tens of thousands of microelectrodes with a pitch below 20um, what gives subcellular resolution and allows the measurement of each neuron by more than one electrode. However, recording the signals captured by all this electrodes is challenging, and typically only a reduced portion of the electrodes (<10%) can be recorded.
In this project the student will try to solve the different optimization problems that arise during the design of a MEA, such as the selection of the best recording electrodes and the interconnection of these electrodes to the on-chip analog-to-digital converters. The project can also include a section about neural signal compression, depending on the interests and background of the student.
Preferred skills: - Background including mathematical optimization - MATLAB - C++ (ideally also Qt Creator)
Not specified
Dr. Fernando Cardes (Fernando.cardes@bsse.ethz.ch)
Dr. Fernando Cardes (Fernando.cardes@bsse.ethz.ch)