Brincat Scott L, Connor Charles E
Zanvyl Krieger Mind/Brain Institute, Department of Neuroscience, Johns Hopkins University, Baltimore, Maryland 21218, USA.
Neuron. 2006 Jan 5;49(1):17-24. doi: 10.1016/j.neuron.2005.11.026.
How does the brain synthesize low-level neural signals for simple shape parts into coherent representations of complete objects? Here, we present evidence for a dynamic process of object part integration in macaque posterior inferotemporal cortex (IT). Immediately after stimulus onset, neural responses carried information about individual object parts (simple contour fragments) only. Subsequently, information about specific multipart configurations emerged, building gradually over the course of approximately 60 ms, producing a sparser and more explicit representation of object shape. We show that this gradual transformation can be explained by a recurrent network process that effectively compares parts signals across neurons to generate inferences about multipart shape configurations.
大脑是如何将简单形状部分的低级神经信号合成完整物体的连贯表征的?在这里,我们提供了猕猴后颞下皮质(IT)中物体部分整合的动态过程的证据。刺激开始后,神经反应仅携带有关单个物体部分(简单轮廓片段)的信息。随后,有关特定多部分配置的信息出现,在大约60毫秒的过程中逐渐形成,产生了更稀疏、更明确的物体形状表征。我们表明,这种逐渐转变可以通过一个循环网络过程来解释,该过程有效地比较神经元之间的部分信号,以生成关于多部分形状配置的推断。