Ashtiani Matin N, Kheradpisheh Saeed R, Masquelier Timothée, Ganjtabesh Mohammad
Department of Computer Science, School of Mathematics, Statistics, and Computer Science, University of TehranTehran, Iran.
School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM)Tehran, Iran.
Front Psychol. 2017 Jul 25;8:1261. doi: 10.3389/fpsyg.2017.01261. eCollection 2017.
The human visual system contains a hierarchical sequence of modules that take part in visual perception at different levels of abstraction, i.e., superordinate, basic, and subordinate levels. One important question is to identify the "entry" level at which the visual representation is commenced in the process of object recognition. For a long time, it was believed that the basic level had a temporal advantage over two others. This claim has been challenged recently. Here we used a series of psychophysics experiments, based on a rapid presentation paradigm, as well as two computational models, with bandpass filtered images of five object classes to study the processing order of the categorization levels. In these experiments, we investigated the type of visual information required for categorizing objects in each level by varying the spatial frequency bands of the input image. The results of our psychophysics experiments and computational models are consistent. They indicate that the different spatial frequency information had different effects on object categorization in each level. In the absence of high frequency information, subordinate and basic level categorization are performed less accurately, while the superordinate level is performed well. This means that low frequency information is sufficient for superordinate level, but not for the basic and subordinate levels. These finer levels rely more on high frequency information, which appears to take longer to be processed, leading to longer reaction times. Finally, to avoid the ceiling effect, we evaluated the robustness of the results by adding different amounts of noise to the input images and repeating the experiments. As expected, the categorization accuracy decreased and the reaction time increased significantly, but the trends were the same. This shows that our results are not due to a ceiling effect. The compatibility between our psychophysical and computational results suggests that the temporal advantage of the superordinate (resp. basic) level to basic (resp. subordinate) level is mainly due to the computational constraints (the visual system processes higher spatial frequencies more slowly, and categorization in finer levels depends more on these higher spatial frequencies).
人类视觉系统包含一系列分层的模块，这些模块在不同抽象层次（即上级、基本和下级层次）参与视觉感知。一个重要问题是确定在物体识别过程中视觉表征开始的“入口”层次。长期以来，人们认为基本层次在时间上比其他两个层次具有优势。这一观点最近受到了挑战。在此，我们基于快速呈现范式进行了一系列心理物理学实验，并使用了两个计算模型，利用五类物体的带通滤波图像来研究分类层次的处理顺序。在这些实验中，我们通过改变输入图像的空间频率带，研究了每个层次对物体进行分类所需的视觉信息类型。我们的心理物理学实验和计算模型的结果是一致的。结果表明，不同的空间频率信息对每个层次的物体分类有不同影响。在没有高频信息的情况下，下级和基本层次的分类准确性较低，而上位层次的分类效果良好。这意味着低频信息足以进行上位层次的分类，但不足以进行基本和下级层次的分类。这些更精细的层次更多地依赖高频信息，而高频信息的处理似乎需要更长时间，导致反应时间更长。最后，为了避免天花板效应，我们通过向输入图像添加不同量的噪声并重复实验来评估结果的稳健性。正如预期的那样，分类准确性下降，反应时间显著增加，但趋势相同。这表明我们的结果并非由于天花板效应。我们的心理物理学和计算结果之间的兼容性表明，上级（相应地，基本）层次相对于基本（相应地，下级）层次的时间优势主要是由于计算限制（视觉系统处理更高空间频率的速度更慢，更精细层次的分类更多地依赖于这些更高的空间频率）。
