Nowadays, it is widely believed that the temporal structure of the auditory nerve fibers' response to sound stimuli plays an important role in auditory perception. An influential hypothesis is that information is extracted from this temporal structure by neural operations akin to an autocorrelation algorithm. The goal of the present work was to test this hypothesis. The stimuli consisted of sequences of unipolar clicks that were high-pass filtered and mixed with low-pass noise so as to exclude spectral cues. In experiment 1, "interfering" clicks were inserted in an otherwise periodic (isochronous) click sequence. Each click belonging to the periodic sequence was followed, after a random portion of the period, by one interfering click. This disrupted the detection of temporal regularity, even when the interfering clicks were 5 dB less intense than the periodic clicks. Experiments 2-4 used click sequences that showed a single peak in their autocorrelation functions. For some sequences, this peak originated from "first-order" temporal regularities, that is from the temporal relations between consecutive clicks. For other sequences, the peak originated instead from "second-order" regularities, relative to nonconsecutive clicks. The detection of second-order regularities appeared to be much more difficult than the detection of comparable first-order regularities. Overall, these results do not tally with the current autocorrelation models of temporal processing. They suggest that the extraction of temporal information from a group of closely spaced spectral components makes no use of time intervals between nonconsecutive peaks of the amplitude envelope.