对自然对象的感知和神经反应的数据驱动分析揭示了人类视觉认知的组织原则
David M Watson1, Timothy J Andrews2
1Department of Psychology and York Neuroimaging Centre, University of York, York, UK, YO10 5DD david.watson@york.ac.uk.
概括
视觉皮层的组织反映了自然对象的统计特性. 一个数据驱动模型准确地预测了从对象感知中获得的神经反应,揭示了高效的信息编码.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 计算机视觉 计算机视觉
背景情况:
- 由于在呈现自然物体方面的实验限制,理解视觉皮层组织是具有挑战性的.
- 当前的实验设计可能会通过使用实验者定义的刺激条件来限制神经数据的解释.
研究的目的:
- 用数据驱动方法揭示视觉大脑的功能组织,采用自然物体的系统样本.
- 探索对物体的感知和神经反应如何在视觉皮层中相互关联.
主要方法:
- 利用THINGS倡议的图像进行系统的自然物体采样.
- 应用了部分最小平方回归 (PLSR) 来预测全脑功能磁共振成像 (fMRI) 响应的感知相似性判断.
- 集成的缩小维度来分析神经和感知数据.
主要成果:
- 一个PLSR模型准确地预测了视觉皮层中的神经反应,只有少数组件.
- 在两个半球中确定了光滑,分级的神经拓.
- 发现这些组件捕获了对象的属性,如动态性,大小和类别,但与现有的理论模型不一致.
结论:
- 视觉皮层以统计学上高效的方式编码信息,反映对象的自然变化.
- 视觉大脑的组织似乎是基于自然界固有的统计性质.
- 这些发现挑战了以前对对象感知的看法,并提出了一个数据驱动的,统计学上高效的模型.
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