Suppr超能文献

统计学习的顺序取决于感知不确定性。

Order of statistical learning depends on perceptive uncertainty.

作者信息

Daikoku Tatsuya, Yumoto Masato

机构信息

International Research Center for Neurointelligence, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan.

Center for Brain, Mind and KANSEI Sciences Research, Hiroshima University, Hiroshima, Japan.

出版信息

Curr Res Neurobiol. 2023 Mar 1;4:100080. doi: 10.1016/j.crneur.2023.100080. eCollection 2023.

Abstract

Statistical learning (SL) is an innate mechanism by which the brain automatically encodes the -th order transition probability (TP) of a sequence and grasps the uncertainty of the TP distribution. Through SL, the brain predicts a subsequent event ( ) based on the preceding events ( ) that have a length of ". It is now known that uncertainty modulates prediction in top-down processing by the human predictive brain. However, the manner in which the human brain modulates the order of SL strategies based on the degree of uncertainty remains an open question. The present study examined how uncertainty modulates the neural effects of SL and whether differences in uncertainty alter the order of SL strategies. It used auditory sequences in which the uncertainty of sequential information is manipulated based on the conditional entropy. Three sequences with different TP ratios of 90:10, 80:20, and 67:33 were prepared as low-, intermediate, and high-uncertainty sequences, respectively (conditional entropy: 0.47, 0.72, and 0.92 bit, respectively). Neural responses were recorded when the participants listened to the three sequences. The results showed that stimuli with lower TPs elicited a stronger neural response than those with higher TPs, as demonstrated by a number of previous studies. Furthermore, we found that participants adopted higher-order SL strategies in the high uncertainty sequence. These results may indicate that the human brain has an ability to flexibly alter the order based on the uncertainty. This uncertainty may be an important factor that determines the order of SL strategies. Particularly, considering that a higher-order SL strategy mathematically allows the reduction of uncertainty in information, we assumed that the brain may take higher-order SL strategies when encountering high uncertain information in order to reduce the uncertainty. The present study may shed new light on understanding individual differences in SL performance across different uncertain situations.

摘要

统计学习(SL)是一种内在机制,通过该机制大脑自动对序列的第 - 阶转移概率(TP)进行编码,并掌握TP分布的不确定性。通过统计学习,大脑根据长度为“ ”的先前事件( )预测后续事件( )。现在已知不确定性会在人类预测性大脑的自上而下处理中调节预测。然而,人类大脑根据不确定性程度调节统计学习策略顺序的方式仍然是一个悬而未决的问题。本研究考察了不确定性如何调节统计学习的神经效应,以及不确定性的差异是否会改变统计学习策略的顺序。研究使用了基于条件熵操纵序列信息不确定性的听觉序列。分别准备了TP比率为90:10、80:20和67:33的三个序列作为低、中、高不确定性序列(条件熵分别为0.47、0.72和0.92比特)。当参与者聆听这三个序列时记录神经反应。结果表明,与先前许多研究一致,具有较低TP的刺激比具有较高TP的刺激引发更强的神经反应。此外,我们发现参与者在高不确定性序列中采用了更高阶的统计学习策略。这些结果可能表明人类大脑有能力根据不确定性灵活改变顺序。这种不确定性可能是决定统计学习策略顺序的一个重要因素。特别是,考虑到高阶统计学习策略在数学上允许减少信息中的不确定性,我们假设大脑在遇到高不确定信息时可能会采用高阶统计学习策略以减少不确定性。本研究可能为理解不同不确定情况下统计学习表现的个体差异提供新的线索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/25cc/10011828/721ddd949c2c/ga1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验