Statistical Learning of Frequent Distractor Locations in Visual Search Involves Regional Signal Suppression in Early Visual Cortex

视皮层 心理学 统计学习 视觉系统 神经科学 皮质(解剖学) 视觉记忆 视觉搜索 认知心理学 认知 计算机科学 人工智能
作者
Bei Zhang,Ralph Weidner,Fredrik Allenmark,Sabine Bertleff,Gereon R. Fink,Zhuanghua Shi,Hermann J. Müller
出处
期刊:Cerebral Cortex [Oxford University Press]
卷期号:32 (13): 2729-2744 被引量:36
标识
DOI:10.1093/cercor/bhab377
摘要

Abstract Observers can learn locations where salient distractors appear frequently to reduce potential interference—an effect attributed to better suppression of distractors at frequent locations. But how distractor suppression is implemented in the visual cortex and within the frontoparietal attention networks remains unclear. We used fMRI and a regional distractor-location learning paradigm with two types of distractors defined in either the same (orientation) or a different (color) dimension to the target to investigate this issue. fMRI results showed that BOLD signals in early visual cortex were significantly reduced for distractors (as well as targets) occurring at the frequent versus rare locations, mirroring behavioral patterns. This reduction was more robust with same-dimension distractors. Crucially, behavioral interference was correlated with distractor-evoked visual activity only for same- (but not different-) dimension distractors. Moreover, with different- (but not same-) dimension distractors, a color-processing area within the fusiform gyrus was activated more when a distractor was present in the rare region versus being absent and more with a distractor in the rare versus frequent locations. These results support statistical learning of frequent distractor locations involving regional suppression in early visual cortex and point to differential neural mechanisms of distractor handling with different- versus same-dimension distractors.
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
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
传奇3应助一个人的街采纳,获得10
刚刚
1秒前
aaccc发布了新的文献求助10
1秒前
2秒前
11414发布了新的文献求助10
2秒前
今天会有好事发生完成签到 ,获得积分10
2秒前
乌鱼子发布了新的文献求助10
3秒前
怀安完成签到,获得积分10
3秒前
eas发布了新的文献求助10
4秒前
全民饿人发布了新的文献求助10
4秒前
4秒前
5秒前
6秒前
7秒前
orixero应助汤圆软软软采纳,获得10
7秒前
7秒前
领导范儿应助秀丽的咖啡采纳,获得10
7秒前
情怀应助汤圆软软软采纳,获得10
7秒前
wanci应助汤圆软软软采纳,获得10
7秒前
ding应助汤圆软软软采纳,获得10
7秒前
7秒前
7秒前
7秒前
7秒前
7秒前
7秒前
酷波er应助aaccc采纳,获得10
8秒前
8秒前
10ml离心管完成签到,获得积分10
9秒前
锤锤发布了新的文献求助10
10秒前
10秒前
今后应助mokiduka采纳,获得10
11秒前
liben发布了新的文献求助10
12秒前
12秒前
orixero应助ycl采纳,获得10
12秒前
雨筠发布了新的文献求助10
13秒前
13秒前
有猫腻完成签到,获得积分10
13秒前
Ds发布了新的文献求助10
14秒前
15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
Rosenblum, Global Change Biology 800
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Physiologic specialization in Peronospora manshurica 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7777297
求助须知:如何正确求助?哪些是违规求助? 9318392
关于积分的说明 20363957
捐赠科研通 7364423
什么是DOI,文献DOI怎么找? 3318922
关于科研通互助平台的介绍 2466578
邀请新用户注册赠送积分活动 2334129