Schwartz Odelia, Giraldo Luis Gonzalo Sanchez
Department of Computer Science, University of Miami, Miami, FL,
J Vis. 2017 Mar 1;17(3):13. doi: 10.1167/17.3.13.
Central to behavior and cognition is the way that sensory stimuli are represented in neural systems. The distributions over such stimuli enjoy rich structure; however, how the brain captures and exploits these regularities is unclear. Here, we consider different sources of perhaps the most prevalent form of structure, namely hierarchies, in one of its most prevalent cases, namely the representation of images. We review experimental approaches across a range of subfields, spanning inference, memory recall, and visual adaptation, to investigate how these constrain hierarchical representations. We also discuss progress in building hierarchical models of the representation of images-this has the potential to clarify how the structure of the world is reflected in biological systems. We suggest there is a need for a closer embedding of recent advances in machine learning and computer vision into the design and interpretation of experiments, notably by utilizing the understanding of the structure of natural scenes and through the creation of hierarchically structured synthetic stimuli.
行为和认知的核心在于神经系统中感觉刺激的呈现方式。这些刺激的分布具有丰富的结构；然而，大脑如何捕捉和利用这些规律尚不清楚。在这里，我们考虑了结构最普遍的形式（即层次结构）的不同来源，在其最普遍的一种情况下，即图像的表征。我们回顾了一系列子领域的实验方法，包括推理、记忆回忆和视觉适应，以研究这些方法如何约束层次表征。我们还讨论了构建图像表征层次模型的进展——这有可能阐明世界的结构是如何在生物系统中得到反映的。我们认为，有必要将机器学习和计算机视觉的最新进展更紧密地融入实验的设计和解释中，特别是通过利用对自然场景结构的理解以及创建层次结构化的合成刺激来实现。
