首页> 外文期刊>中国神经再生研究(英文版) >Brain functional network connectivity based on a visual task:visual information processing-related brain regions are signiifcantly activated in the task state
【24h】

Brain functional network connectivity based on a visual task:visual information processing-related brain regions are signiifcantly activated in the task state

机译:基于视觉任务的大脑功能网络连通性:与视觉信息处理相关的大脑区域在任务状态下被显着激活

获取原文
获取原文并翻译 | 示例
       

摘要

It is not clear whether the method used in functional brain-network related research can be applied to explore the feature binding mechanism of visual perception. In this study, we inves-tigated feature binding of color and shape in visual perception. Functional magnetic resonance imaging data were collected from 38 healthy volunteers at rest and while performing a visual perception task to construct brain networks active during resting and task states. Results showed that brain regions involved in visual information processing were obviously activated during the task. The components were partitioned using a greedy algorithm, indicating the visual network existed during the resting state.Z-values in the vision-related brain regions were calculated, conifrming the dynamic balance of the brain network. Connectivity between brain regions was determined, and the result showed that occipital and lingual gyri were stable brain regions in the visual system network, the parietal lobe played a very important role in the binding process of color features and shape features, and the fusiform and inferior temporal gyri were crucial for processing color and shape information. Experimental ifndings indicate that understanding visual feature binding and cognitive processes will help establish computational models of vision, improve image recognition technology, and provide a new theoretical mechanism for feature binding in visual perception.
机译:尚不清楚功能性脑网络相关研究中使用的方法是否可用于探索视觉知觉的特征结合机制。在这项研究中,我们研究了视觉感知中颜色和形状的特征绑定。功能性磁共振成像数据是从38位健康的静息志愿者那里收集的,它们在执行视觉感知任务时可以构建在休息和任务状态下活跃的大脑网络。结果显示,在执行任务期间,涉及视觉信息处理的大脑区域明显被激活。使用贪婪算法对组件进行划分,表明视觉网络在静止状态下存在。计算与视觉有关的大脑区域的Z值,确认大脑网络的动态平衡。确定了大脑区域之间的连通性,结果表明枕叶和舌状回在视觉系统网络中是稳定的大脑区域,顶叶在颜色特征和形状特征以及梭形和下等的结合过程中起着非常重要的作用。颞回对于处理颜色和形状信息至关重要。实验结果表明,了解视觉特征绑定和认知过程将有助于建立视觉计算模型,改进图像识别技术,并为视觉感知中的特征绑定提供新的理论机制。

著录项

  • 来源
    《中国神经再生研究(英文版)》 |2015年第2期|298-307|共10页
  • 作者单位

    School of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, Shanxi Province, China;

    School of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, Shanxi Province, China;

    School of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, Shanxi Province, China;

    School of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, Shanxi Province, China;

    School of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, Shanxi Province, China;

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-19 03:44:31
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号