Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany.
Berlin School of Mind and Brain, Faculty of Philosophy, Humboldt-Universität zu Berlin, Berlin, Germany.
Nat Hum Behav. 2022 Jun;6(6):796-811. doi: 10.1038/s41562-022-01302-0. Epub 2022 Feb 24.
To interact with objects in complex environments, we must know what they are and where they are in spite of challenging viewing conditions. Here, we investigated where, how and when representations of object location and category emerge in the human brain when objects appear on cluttered natural scene images using a combination of functional magnetic resonance imaging, electroencephalography and computational models. We found location representations to emerge along the ventral visual stream towards lateral occipital complex, mirrored by gradual emergence in deep neural networks. Time-resolved analysis suggested that computing object location representations involves recurrent processing in high-level visual cortex. Object category representations also emerged gradually along the ventral visual stream, with evidence for recurrent computations. These results resolve the spatiotemporal dynamics of the ventral visual stream that give rise to representations of where and what objects are present in a scene under challenging viewing conditions.
为了在复杂环境中与物体交互,我们必须知道它们是什么,以及它们在有挑战性的观察条件下的位置。在这里,我们使用功能磁共振成像、脑电图和计算模型的组合,研究了当物体出现在杂乱的自然场景图像上时,人类大脑中物体位置和类别代表是如何、何时出现的。我们发现位置代表沿着腹侧视觉流向外侧枕叶复合体出现,这与深度神经网络中逐渐出现的位置代表相呼应。时分辨析表明,计算物体位置代表涉及高级视觉皮层中的递归处理。物体类别代表也沿着腹侧视觉流逐渐出现,有证据表明存在递归计算。这些结果解决了腹侧视觉流产生在有挑战性的观察条件下表示场景中物体位置和物体存在的代表的时空动态。