Integrated effects of top-down attention and statistical learning during visual search: An EEG study

提示语 N2pc 心理学 脑电图 视觉搜索 认知心理学 注意力控制 视觉空间注意 自上而下和自下而上的设计 控制(管理) 视觉注意 神经科学 计算机科学 感知 认知 人工智能 软件工程
作者
Carola Dolci,C. Nico Boehler,Elisa Santandrea,Anneleen Dewulf,Suliann Ben Hamed,Emiliano Macaluso,Leonardo Chelazzi,Einat Rashal
出处
期刊:Attention, perception & psychophysics [Springer Science+Business Media]
卷期号:85 (6): 1819-1833 被引量:7
标识
DOI:10.3758/s13414-023-02728-y
摘要

Abstract The present study aims to investigate how the competition between visual elements is solved by top-down and/or statistical learning (SL) attentional control (AC) mechanisms when active together. We hypothesized that the “winner” element that will undergo further processing is selected either by one AC mechanism that prevails over the other, or by the joint activity of both mechanisms. To test these hypotheses, we conducted a visual search experiment that combined an endogenous cueing protocol (valid vs. neutral cue) and an imbalance of target frequency distribution across locations (high- vs. low-frequency location). The unique and combined effects of top-down control and SL mechanisms were measured on behaviour and amplitudes of three evoked-response potential (ERP) components (i.e., N2pc, P1, CNV) related to attentional processing. Our behavioural results showed better performance for validly cued targets and for targets in the high-frequency location. The two factors were found to interact, so that SL effects emerged only in the absence of top-down guidance. Whereas the CNV and P1 only displayed a main effect of cueing, for the N2pc we observed an interaction between cueing and SL, revealing a cueing effect for targets in the low-frequency condition, but not in the high-frequency condition. Thus, our data support the view that top-down control and SL work in a conjoint, integrated manner during target selection. In particular, SL mechanisms are reduced or even absent when a fully reliable top-down guidance of attention is at play.

科研通智能强力驱动
Strongly Powered by AbleSci AI
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
dounai发布了新的文献求助10
1秒前
1秒前
G1234发布了新的文献求助10
1秒前
2秒前
2秒前
小熊吖完成签到 ,获得积分10
3秒前
苏世誉完成签到,获得积分10
3秒前
林宇川完成签到,获得积分10
4秒前
大白发布了新的文献求助10
5秒前
食分子发布了新的文献求助10
6秒前
tuantuan发布了新的文献求助10
7秒前
Chio发布了新的文献求助10
7秒前
8秒前
无心的天真完成签到 ,获得积分10
9秒前
JSY发布了新的文献求助10
9秒前
无昵称完成签到 ,获得积分10
10秒前
时尚的大山应助chenjzhuc采纳,获得30
10秒前
丘比特应助食分子采纳,获得10
13秒前
科研小辉完成签到,获得积分10
13秒前
端庄的如霜完成签到,获得积分10
13秒前
谢耳朵完成签到 ,获得积分10
14秒前
嘟嘟豆806完成签到 ,获得积分0
14秒前
Yuang完成签到 ,获得积分10
14秒前
15秒前
陈龙完成签到,获得积分10
16秒前
科研通AI6.3应助波力海苔采纳,获得10
17秒前
17秒前
李不乐完成签到,获得积分10
17秒前
枯叶灬风完成签到,获得积分10
18秒前
苏苏完成签到,获得积分10
18秒前
zdw完成签到,获得积分10
20秒前
斯文香彤完成签到,获得积分10
20秒前
20秒前
20秒前
Ao完成签到,获得积分10
21秒前
淡定曼寒发布了新的文献求助10
21秒前
董昌铭发布了新的文献求助10
23秒前
TangQQ完成签到,获得积分10
23秒前
24秒前
程程完成签到 ,获得积分10
24秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Modern Epidemiology, Fourth Edition 5000
Handbook of pharmaceutical excipients, Ninth edition 5000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Social Cognition: Understanding People and Events 1000
Polymorphism and polytypism in crystals 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6030180
求助须知:如何正确求助?哪些是违规求助? 7704658
关于积分的说明 16192176
捐赠科研通 5177088
什么是DOI,文献DOI怎么找? 2770430
邀请新用户注册赠送积分活动 1753873
关于科研通互助平台的介绍 1639385