Energy Efficient Low-Noise Multichannel Neural Amplifier in Submicron CMOS Process

This paper presents a low noise low power neural recording amplifier that occupies a very small silicon area and is suitable to integrate with multielectrode arrays in cortical implants. We analyze main problems in neural recording systems processed in modern submicron technologies, i.e., leakage currents, ability to obtain very large and precisely controlled MOS based resistances and spread of the main system parameters from channel to channel. We also introduce methods allowing to mitigate them. Finally, we present methods allowing to calculate optimal channel dimensions of the recording channel's input transistors in order to obtain the lowest Input Referred Noise (IRN) for given power and area requirements. The proposed methodology has been applied in the 8-channel integrated recording ASIC dedicated to the broad range of neurobiology experiments. Each of the recording channels is equipped with the control register that enables to set main channel parameters independently. Thanks to this functionality, the user is capable of setting lower cut-off frequency within the range of 300 mHz-900 Hz. The upper cut-off frequency can be switched either to 30 Hz-290 Hz or 9 kHz, while the voltage gain can be set either to 260 V/V or 1000 V/V. A single recording channel is supplied with 1.8 V and consumes only 11 μW of power, while its input referred noise is equal to 4.4 μV resulting in NEF equal to 4.1.