Prediction Signatures in the Brain: Semantic Pre-Activation during Language Comprehension

400奈米 名词 背景(考古学) 脑磁图 计算机科学 动词 语义记忆 语义学(计算机科学) 自然语言处理 人工智能 心理学 认知 脑电图 事件相关电位 神经科学 生物 古生物学 程序设计语言
作者
Burkhard Maess,Fahimeh Mamashli,Jonas Obleser,Liisa Helle,Angela D. Friederici
出处
期刊:Frontiers in Human Neuroscience [Frontiers Media]
卷期号:10 被引量:43
标识
DOI:10.3389/fnhum.2016.00591
摘要

There is broad agreement that context-based predictions facilitate lexical-semantic processing. A robust index of semantic prediction during language comprehension is an evoked response, known as the N400, whose amplitude is modulated as a function of semantic context. However, the underlying neural mechanisms that utilize relations of the prior context and the embedded word within it are largely unknown. We measured magnetoencephalography (MEG) data while participants were listening to simple German sentences in which the verbs were either highly predictive for the occurrence of a particular noun (i.e., provided context) or not. The identical set of nouns was presented in both conditions. Hence, differences for the evoked responses of the nouns can only be due to differences in the earlier context. We observed a reduction of the N400 response for highly predicted nouns. Interestingly, the opposite pattern was observed for the preceding verbs: highly predictive (that is more informative) verbs yielded stronger neural magnitude compared to less predictive verbs. A negative correlation between the N400 effect of the verb and that of the noun was found in a distributed brain network, indicating an integral relation between the predictive power of the verb and the processing of the subsequent noun. This network consisted of left hemispheric superior and middle temporal areas and a subcortical area; the parahippocampus. Enhanced activity for highly predictive relative to less predictive verbs, likely reflects establishing semantic features associated with the expected nouns, that is a pre-activation of the expected nouns.

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
123完成签到,获得积分20
刚刚
龙九局完成签到 ,获得积分10
刚刚
JamesPei应助Lifel采纳,获得10
刚刚
1秒前
Nora完成签到 ,获得积分10
1秒前
YH发布了新的文献求助10
1秒前
杨洋完成签到 ,获得积分10
2秒前
2秒前
搜集达人应助科研通管家采纳,获得10
2秒前
深情安青应助科研通管家采纳,获得10
2秒前
FashionBoy应助科研通管家采纳,获得10
2秒前
领导范儿应助科研通管家采纳,获得10
2秒前
sciq完成签到,获得积分10
2秒前
wulanshu应助科研通管家采纳,获得10
2秒前
2秒前
隐形曼青应助科研通管家采纳,获得10
2秒前
Owen应助科研通管家采纳,获得10
2秒前
图图完成签到,获得积分10
2秒前
深情安青应助科研通管家采纳,获得10
2秒前
2秒前
NexusExplorer应助科研通管家采纳,获得10
2秒前
2秒前
3秒前
3秒前
3秒前
3秒前
3秒前
3秒前
3秒前
sssssR发布了新的文献求助10
3秒前
3秒前
3秒前
3秒前
冬眠完成签到,获得积分10
4秒前
Dr.c完成签到,获得积分10
4秒前
77发布了新的文献求助10
4秒前
5秒前
5秒前
斯文败类应助HOLLY采纳,获得10
5秒前
6秒前
高分求助中
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
天津市智库成果选编 600
Climate change and sports: Statistics report on climate change and sports 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Organic Reactions Volume 118 400
A Foreign Missionary on the Long March: The Unpublished Memoirs of Arnolis Hayman of the China Inland Mission 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6460759
求助须知:如何正确求助?哪些是违规求助? 8269434
关于积分的说明 17627564
捐赠科研通 5530834
什么是DOI,文献DOI怎么找? 2906292
邀请新用户注册赠送积分活动 1883097
关于科研通互助平台的介绍 1728671