Energy efficient low-noise neural recording amplifier with enhanced noise efficiency factor.

This paper presents a neural recording amplifier array suitable for large-scale integration with multielectrode arrays in very low-power microelectronic cortical implants. The proposed amplifier is one of the most energy-efficient structures reported to date, which theoretically achieves an effective noise efficiency factor (NEF) smaller than the limit that can be achieved by any existing amplifier topology, which utilizes a differential pair input stage. The proposed architecture, which is referred to as a partial operational transconductance amplifier sharing architecture, results in a significant reduction of power dissipation as well as silicon area, in addition to the very low NEF. The effect of mismatch on crosstalk between channels and the tradeoff between noise and crosstalk are theoretically analyzed. Moreover, a mathematical model of the nonlinearity of the amplifier is derived, and its accuracy is confirmed by simulations and measurements. For an array of four neural amplifiers, measurement results show a midband gain of 39.4 dB and a -3-dB bandwidth ranging from 10 Hz to 7.2 kHz. The input-referred noise integrated from 10 Hz to 100 kHz is measured at 3.5 μVrms and the power consumption is 7.92 μW from a 1.8-V supply, which corresponds to NEF = 3.35. The worst-case crosstalk and common-mode rejection ratio within the desired bandwidth are - 43.5 dB and 70.1 dB, respectively, and the active silicon area of each amplifier is 256 μm × 256 μm in 0.18-μm complementary metal-oxide semiconductor technology.