Statistical learning dynamically shapes auditory perception

统计学习动态地塑造听觉感知

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Abstract

Humans and other animals use information about how likely it is for something to happen. The absolute and relative probability of an event influences a remarkable breadth of behaviors, from foraging for food to comprehending linguistic constructions -- even when these probabilities are learned implicitly. It is less clear how, and under what circumstances, statistical learning of simple probabilities might drive changes in perception and cognition. Here, across a series of 29 experiments, we probe listeners' sensitivity to task-irrelevant changes in the probability distribution of tones' acoustic frequency across tone-in-noise detection and tone duration decisions. We observe that the task-irrelevant frequency distribution influences the ability to detect a sound and the speed with which perceptual decisions about its duration are made. The shape of the probability distribution, its range, and a tone's relative position within that range impact observed patterns of suppression and enhancement of tone detection and decision making. Perceptual decisions are also modulated by a newly discovered perceptual bias, with lower frequencies in the distribution more often and more rapidly perceived as longer, and higher frequencies as shorter. Perception is sensitive to rapid distribution changes, but distributional learning from previous probability distributions also carries over. In fact, massed exposure to a single point along the dimension results in seemingly maladaptive loss of sensitivity - occurring entirely in the absence of feedback or reward - along a range of subsequently encountered frequencies. This points to a gain mechanism that suppresses sensitivity to regions along a perceptual dimension that are less likely to be encountered.

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