中国神经再生研究(英文版) ›› 2015, Vol. 10 ›› Issue (10): 1622-1627.doi: 10.4103/1673-5374.167761

• 原著:脑损伤修复保护与再生 • 上一篇    下一篇

初级视皮质经分类器可成功将不同的大脑响应区分辨别

  

  • 收稿日期:2015-07-27 出版日期:2015-10-28 发布日期:2015-10-28
  • 基金资助:

    国家自然科学基金(31070882)

Decoding brain responses to pixelized images in the primary visual cortex: implications for visual cortical prostheses

Bing-bing Guo1, 2, Xiao-lin Zheng1, Zhen-gang Lu2, Xing Wang1, Zheng-qin Yin3, Wen-sheng Hou1, *, Ming Meng2   

  1. 1 Department of Biomedical Engineering, Chongqing University, Chongqing, China
    2 Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
    3 Key Lab of Visual Damage and Regeneration & Restoration, Third Military Medical University, Chongqing, China
  • Received:2015-07-27 Online:2015-10-28 Published:2015-10-28
  • Contact: Wen-sheng Hou, M.D.,w.s.hou@cqu.edu.cn
  • Supported by:

    This study was supported by the National Natural Science Foundation of China, No. 31070758, 31271060 and the Natural Science Foundation of Chongqing in China, No. cstc2013jcyjA10085.

摘要:

前视皮质视觉假体仅能提供低分辨率的视觉感受,假体植入者只能“看见”像素化图像。能否在初级视皮质(视皮质视觉假体植入区域)获得不同像素化图像诱发的具有差异性的大脑响应尚不清楚。我们利用功能磁共振技术研究正常人对于18幅不同像素化图像的大脑响应,实验的分类器选用属于一般线性分类器的支持向量机,从初级视皮质挑选出100个体素,以4 mm×4 mm×4 mm的体素大小组成大脑响应。多体素模式分析被用于检测所设计的大脑响应是否具有显著差异性,结果发现分类器正确率远远高于随机水平。结果证实,不同像素化图像诱发的具有差异性的大脑响应可以通过4 mm×4 mm×4 mm的体素大小,100个体素阵列在初级视皮质表征出来,实验所用的分类器可成功将不同的大脑响应区分辨别。

关键词: 神经再生, 视皮质假体, 初级视皮质, 电刺激, 低分辨率视觉, 像素化图像, 功能磁共振成像, 体素, 脑激活模式, 国家自然科学基金

Abstract:

Visual cortical prostheses have the potential to restore partial vision. Still limited by the low-resolution visual percepts provided by visual cortical prostheses, implant wearers can currently only “see” pixelized images, and how to obtain the specific brain responses to different pixelized images in the primary visual cortex (the implant area) is still unknown. We conducted a functional magnetic resonance imaging experiment on normal human participants to investigate the brain activation patterns in response to 18 different pixelized images. There were 100 voxels in the brain activation pattern that were selected from the primary visual cortex, and voxel size was 4 mm × 4 mm × 4 mm. Multi-voxel pattern analysis was used to test if these 18 different brain activation patterns were specific. We chose a Linear Support Vector Machine (LSVM) as the classifier in this study. The results showed that the classification accuracies of different brain activation patterns were significantly above chance level, which suggests that the classifier can successfully distinguish the brain activation patterns. Our results suggest that the specific brain activation patterns to different pixelized images can be obtained in the primary visual cortex using a 4 mm × 4 mm × 4 mm voxel size and a 100-voxel pattern.

Key words: nerve regeneration, primary visual cortex, electrical stimulation, visual cortical prosthesis, low resolution vision, pixelized image, functional magnetic resonance imaging, voxel size, neural regeneration, brain activation pattern