A cascading neural loop model is proposed to address the question of how to represent continuous experience. A prediction of the model is that short-term memory decay should exhibit a set of bumps or dips superimposed on a smooth exponential base. The prediction was tested using a Brown- Peterson distractor task, with distractor intervals from 1 to 24 seconds spaced every second apart. In one study with 22 participants, fits of nested regression models indicated that peaking functions with periods near harmonics of 1.6 seconds provided a better description of the data than an exponential function alone. In a replication study with 29 participants, peaking functions with a period of 3.2 seconds provided the best fit. In both studies, 5 % rises above an exponential base were evident near 7, 10 to 11, 13 to 14, and 16 seconds. This short-term memory effect has not been reported before and needs further replication.