Learning a new class of multisensory associations: High-density electrophysiological mapping of the temporal course of audio-visual object processing.

多传感器集成 知觉 心理学 感觉系统 对象(语法) 视觉对象识别的认知神经科学 计算机科学 沟通 感知 神经科学 人工智能
作者
Tiziana Vercillo,Edward G. Freedman,Joshua B. Ewen,Sophie Molholm,John J. Foxe
标识
DOI:10.1101/2021.11.15.468657
摘要

ABSTRACT Multisensory objects that are frequently encountered in the natural environment lead to strong associations across a distributed sensory cortical network, with the end result experience of a unitary percept. Remarkably little is known, however, about the cortical processes sub-serving multisensory object formation and recognition. To advance our understanding in this important domain, the present study investigated the brain processes involved in learning and identification of novel visual-auditory objects. Specifically, we introduce and test a rudimentary three-stage model of multisensory object-formation and processing. Thirty adults were remotely trained for a week to recognize a novel class of multisensory objects (3D shapes paired to complex sounds), and high-density event related potentials (ERPs) were recorded to the corresponding unisensory (shapes or sounds only) and multisensory (shapes and sounds) stimuli, before and after intensive training. We identified three major stages of multisensory processing: 1) an early, multisensory, automatic effect (<100 ms) in occipital areas, related to the detection of simultaneous audiovisual signals and not related to multisensory learning 2) an intermediate object-processing stage (100-200 ms) in occipital and parietal areas, sensitive to the learned multisensory associations and 3) a late multisensory processing stage (>250 ms) that appears to be involved in both object recognition and possibly memory consolidation. Results from this study provide support for multiple stages of multisensory object learning and recognition that are subserved by an extended network of cortical areas.
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
Labubu发布了新的文献求助20
1秒前
极品小亮完成签到,获得积分10
1秒前
Ruuo616完成签到 ,获得积分10
2秒前
fhw完成签到 ,获得积分10
2秒前
YJc发布了新的文献求助30
2秒前
冷艳的白莲完成签到,获得积分10
3秒前
樊书雪完成签到,获得积分10
3秒前
Gemini完成签到,获得积分10
3秒前
阿越完成签到,获得积分0
3秒前
有信心完成签到 ,获得积分10
4秒前
平行线完成签到,获得积分10
5秒前
圆梦完成签到,获得积分20
5秒前
李爱国应助leo采纳,获得10
5秒前
瑞一杯小黄油拿铁完成签到,获得积分10
5秒前
杜杜完成签到,获得积分10
5秒前
FCL完成签到,获得积分10
6秒前
6秒前
科研通AI2S应助大头头很大采纳,获得10
6秒前
繁荣的觅儿完成签到,获得积分10
7秒前
从容傲柏完成签到,获得积分10
7秒前
无限的惜海完成签到 ,获得积分10
8秒前
DezhaoWang完成签到,获得积分10
8秒前
9秒前
范米粒完成签到,获得积分10
9秒前
九湖夷上完成签到,获得积分10
10秒前
Jiangaook完成签到,获得积分10
10秒前
Strongly完成签到,获得积分10
10秒前
ZSJ完成签到,获得积分10
10秒前
含蓄觅山完成签到 ,获得积分10
10秒前
有点儿小库完成签到,获得积分10
10秒前
爽歪歪完成签到,获得积分10
10秒前
长柏完成签到 ,获得积分10
11秒前
任性完成签到,获得积分10
11秒前
Weilu完成签到 ,获得积分10
11秒前
12秒前
zouzhao完成签到,获得积分10
12秒前
12秒前
默默的皮牙子完成签到,获得积分0
13秒前
紫沫完成签到,获得积分10
13秒前
马上动起来完成签到,获得积分10
14秒前
高分求助中
晶体学对称群—如何读懂和应用国际晶体学表 1500
Problem based learning 1000
Constitutional and Administrative Law 1000
Microbially Influenced Corrosion of Materials 500
Die Fliegen der Palaearktischen Region. Familie 64 g: Larvaevorinae (Tachininae). 1975 500
Numerical controlled progressive forming as dieless forming 400
Rural Geographies People, Place and the Countryside 400
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 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5387611
求助须知:如何正确求助?哪些是违规求助? 4509621
关于积分的说明 14032074
捐赠科研通 4420457
什么是DOI,文献DOI怎么找? 2428263
邀请新用户注册赠送积分活动 1420857
关于科研通互助平台的介绍 1400038