When designing an analog front-end for neural interfacing, it is hard to evaluate\nthe interplay of priority features that one must upkeep. Given the competing nature of\ndesign requirements for such systems a good understanding of these trade-offs is necessary.\nLow power, chip size, noise control, gain, temporal resolution and safety are the salient ones.\nThere is a need to expose theses critical features for high performance neural amplifiers\nas the density and performance needs of these systems increases. This review revisits the\nbasic science behind the engineering problem of extracting neural signal from living tissue.\nA summary of architectures and topologies is then presented and illustrated through\na rich set of examples based on the literature. A survey of existing systems is presented for\ncomparison based on prevailing performance metrics.
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