The noise-reduction algorithm as presented in the Methods section “sparse sampling and data recovery”1 seeks to estimate and reduce the spectral contribution of aliased thermal noise, to improve the signal-to-noise ratio (SNR) for highly multiplexed neural recording systems, where implementing adequate antialiasing filters is a challenge. Unfortunately, because of errors described in our corrections3 to a companion paper describing the details of these signal processing algorithms2, the techniques employed do not improve the SNR of high-density acquisition systems limited by noise aliasing beyond what is achievable with conventional band-pass filters.
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