Research data supporting 'Border-ownership-dependent tilt aftereffect for shape defined by binocular disparity and motion parallax'

Research project description: Figure-ground segmentation is a critical function that may be supported by “border-ownership” neural systems that conditionally respond to object borders. We measured border-ownership-dependent tilt aftereffects to figures defined by motion parallax or binocular disparity and found aftereffects for both cues. These effects were transferable between cues, but selective for figure-ground depth order, suggesting that the neural systems supporting figure-ground segmentation have strict depth order selectivity and access to multiple depth cues that are jointly encoded.
Data description: This dataset comprises two .mat files, one for each experiment in the project. Each file contains raw, normalized, and average bias and slope parameters for each subject/condition.

研究项目描述：轮廓-基体分割是一项关键功能，可能由对物体边缘条件性响应的“边界所有权”神经网络系统所支持。我们测量了由运动视差或双眼视差定义的轮廓的边界所有权依赖性倾斜后效，并发现了对两种线索的后效。这些效应在不同线索之间具有可转移性，但对轮廓-基体深度顺序具有选择性，这表明支持轮廓-基体分割的神经网络系统具有严格的深度顺序选择性，并能访问多个共同编码的深度线索。
数据描述：本数据集包含两个.mat文件，每个实验一个。每个文件包含每个受试者/条件原始的、归一化和平均偏差及斜率参数。