Exploiting the 1/f structure of neural signals for the design of integrated neural amplifiers

Neural amplifiers require a large time-constant high-pass filter at ~1 Hz to reject large DC offsets while amplifying low frequency neural signals. This high pass filter is typically realized using large area capacitors and teraohm resistances which makes integration difficult. In this paper, we present a novel topology for a neural amplifier which exploits the (1/f)ⁿ power spectra of local field potentials (LFP). Using a high-pass filter at ~100 Hz, we pre-filter the LFP before amplification. Post digitization, we can recover the LFP signal by building the inverse of the high pass filter in software. We built an array of neural amplifiers based on this principle and tested it on rats chronically implanted with microelectrode arrays. We found that we could recover the initial LFP signal and the power spectral information over time with correlation coefficient greater than 0.94.