亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

How Do Expectations Shape Perception?

感知 概率逻辑 心理学 认知心理学 贝叶斯概率 认知科学 主动感知 计算机科学 人工智能 数据科学 神经科学
作者
Floris P. de Lange,Micha Heilbron,Peter Kok
出处
期刊:Trends in Cognitive Sciences [Elsevier BV]
卷期号:22 (9): 764-779 被引量:920
标识
DOI:10.1016/j.tics.2018.06.002
摘要

Expectations play a strong role in determining the way we perceive the world. Prior expectations can originate from multiple sources of information, and correspondingly have different neural sources, depending on where in the brain the relevant prior knowledge is stored. Recent findings from both human neuroimaging and animal electrophysiology have revealed that prior expectations can modulate sensory processing at both early and late stages, and both before and after stimulus onset. The response modulation can take the form of either dampening the sensory representation or enhancing it via a process of sharpening. Theoretical computational frameworks of neural sensory processing aim to explain how the probabilistic integration of prior expectations and sensory inputs results in perception. Perception and perceptual decision-making are strongly facilitated by prior knowledge about the probabilistic structure of the world. While the computational benefits of using prior expectation in perception are clear, there are myriad ways in which this computation can be realized. We review here recent advances in our understanding of the neural sources and targets of expectations in perception. Furthermore, we discuss Bayesian theories of perception that prescribe how an agent should integrate prior knowledge and sensory information, and investigate how current and future empirical data can inform and constrain computational frameworks that implement such probabilistic integration in perception. Perception and perceptual decision-making are strongly facilitated by prior knowledge about the probabilistic structure of the world. While the computational benefits of using prior expectation in perception are clear, there are myriad ways in which this computation can be realized. We review here recent advances in our understanding of the neural sources and targets of expectations in perception. Furthermore, we discuss Bayesian theories of perception that prescribe how an agent should integrate prior knowledge and sensory information, and investigate how current and future empirical data can inform and constrain computational frameworks that implement such probabilistic integration in perception.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
虚幻雁荷完成签到 ,获得积分10
4秒前
CodeCraft应助墨墨采纳,获得10
11秒前
清爽冬莲完成签到 ,获得积分10
16秒前
42秒前
Qiong完成签到,获得积分10
45秒前
墨墨完成签到,获得积分20
48秒前
江添完成签到,获得积分20
49秒前
量子星尘发布了新的文献求助10
55秒前
1分钟前
江添发布了新的文献求助10
1分钟前
A2QD发布了新的文献求助10
1分钟前
神啊救救我吧完成签到,获得积分10
1分钟前
1分钟前
嗯哼哈哈发布了新的文献求助30
1分钟前
在水一方应助林林采纳,获得10
1分钟前
1分钟前
2分钟前
Kennis发布了新的文献求助10
2分钟前
2分钟前
2分钟前
卡他发布了新的文献求助10
2分钟前
林林发布了新的文献求助10
2分钟前
慕青应助卡他采纳,获得10
2分钟前
Kennis完成签到,获得积分10
2分钟前
2分钟前
Esperanza完成签到,获得积分10
2分钟前
2分钟前
量子星尘发布了新的文献求助10
2分钟前
harvey完成签到,获得积分20
3分钟前
harvey发布了新的文献求助10
3分钟前
大个应助借一颗糖采纳,获得10
3分钟前
Lucas应助认真学习采纳,获得10
3分钟前
3分钟前
借一颗糖发布了新的文献求助10
3分钟前
3分钟前
3分钟前
欣一完成签到,获得积分10
3分钟前
林林发布了新的文献求助10
3分钟前
量子星尘发布了新的文献求助20
3分钟前
欣一发布了新的文献求助10
3分钟前
高分求助中
(禁止应助)【重要!!请各位详细阅读】【科研通的精品贴汇总】 10000
Building Quantum Computers 1000
Nucleophilic substitution in azasydnone-modified dinitroanisoles 500
Molecular Cloning: A Laboratory Manual (Fourth Edition) 500
Social Epistemology: The Niches for Knowledge and Ignorance 500
优秀运动员运动寿命的人文社会学因素研究 500
Encyclopedia of Mathematical Physics 2nd Edition 420
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4242481
求助须知:如何正确求助?哪些是违规求助? 3775964
关于积分的说明 11856298
捐赠科研通 3430719
什么是DOI,文献DOI怎么找? 1882784
邀请新用户注册赠送积分活动 934828
科研通“疑难数据库(出版商)”最低求助积分说明 841227