灵长类下皮层中的物体空间地图
Pinglei Bao1,2, Liang She3, Mason McGill4
1Division of Biology and Biological Engineering, Tianqiao and Chrissy Chen Institute for Neuroscience, Caltech, Pasadena, CA, USA. pbao@caltech.edu.
Nature
|June 5, 2020
概括
研究人员使用深度网络和大脑记录绘制了下皮质 (IT) 的地图. 他们发现了对象空间的粗略地图, 在等级阶段组织视觉对象识别.
科学领域:
- 神经科学
- 计算神经科学
- 计算机视觉
背景情况:
- 下皮质对于物体识别至关重要.
- 尽管面部,身体和场景有专门的区域,但控制IT皮层的组织原则基本上是未知的.
- 信息技术皮层的巨大区域缺乏特定的专业化,这促使人们对一般组织原则进行研究.
研究的目的:
- 研究 IT 皮层的组织原理.
- 了解视觉对象表示是如何在IT皮层组织的.
- 探索深度神经网络与IT皮层组织之间的关系.
主要方法:
- 功能性磁共振成像 (fMRI)
- 微刺激
- 电生理学
- 深度神经网络 (DNN) 用于对象分类
- 构建一个低维物体空间
主要成果:
- 发现IT单元将对象投射到DNN衍生对象空间中的特定轴上.
- 基于偏好的轴,细胞聚集成四个网络,形成对象空间的"地图".
- 这张地图在三个层次阶段持续观察,视图不变度不断增加.
- 这些细胞群集体表现出足够的编码能力来重建物体.
结论:
- 分类选择区域被整合到IT皮层内的更广泛的对象空间地图中.
- 这个物体空间图的尺寸可以从深度神经网络中得出.
- 这为了解物体识别中的IT皮层组织提供了一个统一的框架.
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