Because of well-known nonlinearities in fMRI, responses measured with rapid event-related designs are smaller than responses measured with spaced designs. Surprisingly, no study to date has tested whether rapid designs also change the pattern of responses across different stimulus conditions. Here we report the results of such a test. We measured cortical responses to a flickering checkerboard at different contrasts using rapid and spaced event-related fMRI. The relative magnitude of responses across contrast conditions differed between rapid and spaced designs. Modeling the effect of the rapid design as a scaling of stimulus strength provided a good account of the data. The data were less well fit by a model that scaled the strength of responses. A similar stimulus scaling model has explained effects of neural adaptation, which suggests that adaptation may account for the observed difference between rapid and spaced designs. In a second experiment, we changed the stimulus in ways known to reduce neural adaptation and found much smaller differences between the two designs. Stimulus scaling provides a simple way to account for nonlinearities in event-related fMRI and relate data from rapid designs to data gathered using slower presentation rates. © 2006 Elsevier Inc. All rights reserved.Rapid event-related (ER) functional MRI is one of the most popular methods in cognitive neuroscience. In this method, individual stimuli or trials occur every few seconds or faster. Rapid ER fMRI has several advantages over traditional blocked designs, including the ability to randomize trial types and sort data based upon behavioral responses.Yet, doubt lingers about the generality of results from experiments that use rapid ER fMRI. In particular, it is unclear whether results obtained with rapid event rates will replicate when events occur at slower rates. Almost every study that uses rapid ER designs assumes that fMRI responses show a certain kind of linearity. Specifically, they assume that responses in rapid designs can be predicted by simply adding appropriately placed responses measured in isolation to form the measured fMRI timecourse.Under this temporal superposition assumption, it is straightforward to estimate the average response for each event type, and this response will be identical to what the average response to that event type would be in a spaced design.fMRI data, however, do not obey the assumption of temporal superposition. If superposition holds, then subtracting the response to an individual event from the response to a sequence of two events should yield a response that is identical in shape to the individual response. In actual fMRI data the subtracted response is smaller, often as little as 60-70% of the individual response (Dale and Buckner, 1997;Glover, 1999; McCarthy, 2000, 2001;Boynton and Finney, 2003;Soon et al., 2003;Huettel et al., 2004a;Murray et al., 2006). Similar nonlinearities in response occur in sequences of blocks of events (Boynton et al., 1996;Robson et al., 1998;Vazquez and Noll, 1998;...