The goal of this work is to monitor the activity of neurons in order to better understand information distribution within neural networks. Unfortunately galvanic contact with electrodes can disturb cell growth. Therefore in vitro measurements without cell contact are preferred. Capacitive sensors offer a flexible and noncontact way of implementing a sensor for monitoring neuronal activity. The capacitance of the sensor output is numerically calculated using the simulation tool ANSYS Maxwell simulation. This model was used to simulate the behaviour of the sensor depending on one axon, the location of the action potential and the distance between sensor and axon. Efficient and selective electrical recording of neuronal activity requires multielectrode arrays at the micrometer scale. First test measurements were performed on an axon model with a scaled dimension of 300 : 1 raising the dimensions of the system into the millimeter range. The first element of the amplifier system is an ultra-low bias current operational amplifier (input current of 100 fA max.) One implementation was investigated without any bias current path. For avoiding a polarisation of the sensors a hardware bias current path was implemented at the first stage in two other implementations. One with a resistance of 100kW and the other with two diodes in opposite directions. The simulation shows a typical potential distribution in the sensor decreasing with rising distance between sensor and axon as predicted. First test measurement with a sine-wave as source signal have provided results with a SNR for further signal processing. A measuring system for capacitive monitoring of neuronal cells tested on a dimension of 300 : 1 is presented. Further work will show measurements on an unscaled system with neuronal cell structures grown around a multielectrode array.
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