Towards a state-space geometry of neural responses to natural scenes: A steady-state approach
Towards a state-space geometry of neural responses to natural scenes: A steady-state approach
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DOI：
10.1016/j.neuroimage.2019.116027
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发表时间：
2019-11-01
期刊：
影响因子：
5.7
通讯作者：
Miskovic, Vladimir
中科院分区：
文献类型：
--
作者：
Hansen, Bruce C.;Field, David J.;Miskovic, Vladimir
我们对哺乳动物视觉系统信息处理的理解来自于各种技术，从心理物理学和功能磁共振成像到单单位记录和脑电图。每种技术都为早期视觉系统的处理框架提供了独特的见解。在这里，我们重点关注稳态视觉诱发电位 (SSVEP) 所携带的信息的性质。为了研究 SSVEP 提供的信息，我们向人类参与者展示了一组自然场景，并测量了相对 SSVEP 响应。我们没有关注该信号的特定特征，而是关注可能响应的完整状态空间，并研究如何将诱发的响应映射到该空间。我们的结果表明，可以将 SSVEP 携带的相对高维信号映射到二维空间，且损失很小。我们还表明，一个简单的生物学上合理的模型可以解释该空间中很大一部分可解释方差（类似于 73%）。最后，我们描述了一种测量 SSVEP 图像的可用互信息的技术。这里介绍的技术代表了一种理解 SSVEP 携带的信息性质的新方法。至关重要的是，这种方法是通用的，可以提供一种比较不同神经记录方法结果的方法。总而言之，我们的研究揭示了早期视觉的编码原理，并为理解早期视觉反应空间向连接不同视觉环境的更深层次知识结构的后续转变提供了急需的参考点。
Our understanding of information processing by the mammalian visual system has come through a variety of techniques ranging from psychophysics and fMRI to single unit recording and EEG. Each technique provides unique insights into the processing framework of the early visual system. Here, we focus on the nature of the information that is carried by steady state visual evoked potentials (SSVEPs). To study the information provided by SSVEPs, we presented human participants with a population of natural scenes and measured the relative SSVEP response. Rather than focus on particular features of this signal, we focused on the full state-space of possible responses and investigated how the evoked responses are mapped onto this space. Our results show that it is possible to map the relatively high-dimensional signal carried by SSVEPs onto a 2-dimensional space with little loss. We also show that a simple biologically plausible model can account for a high proportion of the explainable variance (similar to 73%) in that space. Finally, we describe a technique for measuring the mutual information that is available about images from SSVEPs. The techniques introduced here represent a new approach to understanding the nature of the information carried by SSVEPs. Crucially, this approach is general and can provide a means of comparing results across different neural recording methods. Altogether, our study sheds light on the encoding principles of early vision and provides a much needed reference point for understanding subsequent transformations of the early visual response space to deeper knowledge structures that link different visual environments.