Statistical learning dynamically shapes auditory perception.

IF 3.6 1区 心理学 Q1 EDUCATION & EDUCATIONAL RESEARCH
Sahil Luthra, Austin Luor, Adam T Tierney, Frederic Dick, Lori L Holt
{"title":"Statistical learning dynamically shapes auditory perception.","authors":"Sahil Luthra, Austin Luor, Adam T Tierney, Frederic Dick, Lori L Holt","doi":"10.1038/s41539-025-00328-z","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":48503,"journal":{"name":"npj Science of Learning","volume":"10 1","pages":"41"},"PeriodicalIF":3.6000,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12179262/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj Science of Learning","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1038/s41539-025-00328-z","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0

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.

统计学习动态地塑造听觉感知。
人类隐式地接受刺激和事件的概率,但统计学习如何建立影响感知的期望仍不清楚。在29个实验中,我们研究了任务无关分布(定义在声学频率上)对噪声中的音调检测和音调持续时间判断的影响。频率分布的形状和范围影响抑制和增强效果,就像给定音调在范围内的位置一样。感知能迅速适应变化的分布,但过去的分布会影响未来的判断。大量暴露于单一频率影响感知沿着一系列随后遇到的频率。一种新的偏见也出现了:低频被认为更长,高频被认为更短。概率驱动的学习动态地塑造感知,由感觉处理、分布学习和选择性注意的相互影响驱动,塑造一个增益函数,包括适度增强更可能的刺激,以及对不太可能的刺激的强大抑制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
5.40
自引率
7.10%
发文量
29
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信