RESUMO
Event-related potentials (ERPs) acquired during task-free passive listening can be used to study how sensitivity to common pattern repetitions and rare deviations changes over time. These changes are purported to represent the formation and accumulation of precision in internal models that anticipate future states based on probabilistic and/or statistical learning. This study features an unexpected finding; a strong order-dependence in the speed with which deviant responses are elicited that anchors to first learning. Participants heard four repetitions of a sequence in which an equal number of short (30 msec) and long (60 msec) pure tones were arranged into four blocks in which one was common (the standard, p = .875) and the other rare (the deviant, p = .125) with probabilities alternating across blocks. Some participants always heard the sequences commencing with the 30 msec deviant block, and others always with the 60 msec deviant block first. A deviance-detection component known as mismatch negativity (MMN) was extracted from responses and the point in time at which MMN reached maximum amplitude was used as the dependent variable. The results show that if participants heard sequences commencing with the 60 msec deviant block first, the MMN to the 60 msec and 30 msec deviant peaked at an equivalent latency. However, if participants heard sequences commencing with the 30 msec deviant first, the MMN peaked earlier to the 60 msec deviant. Furthermore, while the 30 msec MMN latency did not differ as a function of sequence composition, the 60 msec MMN latency did and was earlier when the sequences began with a 30 msec deviant first. By examining MMN latency effects as a function of age and hearing level it was apparent that the differentiation in 30 msec and 60 msec MMN latency expands with older age and raised hearing threshold due to prolongation of the time taken for the 30 msec MMN to peak. The observations are discussed with reference to how the initial sound composition may tune the auditory system to be more sensitive to different cues (i.e., offset responses vs perceived loudness). The order-effect demonstrates a remarkably powerful anchoring to first learning that might reflect initial tuning to the most valuable discriminating feature within a given listening environment, an effect that defies explanation based on statistical information alone.