Some published cochlear filterbanks are nonlinear but are fitted to animal basilar membrane (BM) responses. Others, like the gammatone, are based on human psychophysical data, but are linear. In this article, a human nonlinear filterbank is constructed by adapting a computational model of animal BM physiology to simulate human BM nonlinearity as measured by psychophysical pulsation-threshold experiments. The approach is based on a dual-resonance nonlinear type of filter whose basic structure was modeled using animal observations. In modeling the pulsation threshold data, the main assumption is that pulsation threshold occurs when the signal and the masker produce comparable excitation, that is the same filter output, at the place of the BM best tuned to the signal frequency. The filter is fitted at a discrete number of best frequencies (BFs) for which psychophysical data are available for a single listener and for an average response of six listeners. The filterbank is then created by linear regression of the resulting parameters to intermediate BFs. The strengths and limitations of the resulting filterbank are discussed. Its suitability for simulating hearing-impaired cochlear responses is also discussed.