Statistical learning dynamically shapes auditory perception - Sahil Luthra; Austin Luor; Adam T. Tierney; Frederic Dick; Lori L. Holt (npj Science of Learning)
Abstract Humans implicitly pick up on probabilities of stimuli and events, yet it remains unclear how statistical learning builds expectations that affect perception. Across 29 experiments, we examine the influence of task-irrelevant distributions—defined across acoustic frequency—on both tone detection in noise and tone duration judgments. The shape and range of the frequency distributions impact suppression and enhancement effects, as does a given tone's position within the range. Perception adapts quickly to changing distributions, but past distributions influence future judgments. Massed exposure to a single frequency impacts perception along a range of subsequently encountered frequencies. A novel bias emerges as well: lower frequencies are perceived as longer and higher ones as shorter. Probability-driven learning dynamically shapes perception, driven by interacting influences of sensory processing, distributional learning, and selective attention that sculpt a gain function involving modest enhancement of more-likely stimuli, and robust suppression of less-likely stimuli.