Montreal Neurological Institute, McGill University School of Medicine, Montreal, QC, Canada H3A 2B4.
Proc Natl Acad Sci U S A. 2012 Apr 17;109(16):E972-80. doi: 10.1073/pnas.1115685109. Epub 2012 Jan 31.
Neurons in the medial superior temporal (MST) area of the primate visual cortex respond selectively to complex motion patterns defined by expansion, rotation, and deformation. Consequently they are often hypothesized to be involved in important behavioral functions, such as encoding the velocities of moving objects and surfaces relative to the observer. However, the computations underlying such selectivity are unknown. In this work we have developed a unique, naturalistic motion stimulus and used it to probe the complex selectivity of MST neurons. The resulting data were then used to estimate the properties of the feed-forward inputs to each neuron. This analysis yielded models that successfully accounted for much of the observed stimulus selectivity, provided that the inputs were combined via a nonlinear integration mechanism that approximates a multiplicative interaction among MST inputs. In simulations we found that this type of integration has the functional role of improving estimates of the 3D velocity of moving objects. As this computation is of general utility for detecting complex stimulus features, we suggest that it may represent a fundamental aspect of hierarchical sensory processing.
灵长类动物视觉皮层中内侧上颞(MST)区域的神经元对由扩展、旋转和变形定义的复杂运动模式有选择性地反应。因此,它们通常被假设参与重要的行为功能,例如对相对于观察者运动的物体和表面的速度进行编码。然而,这种选择性的基础计算仍然未知。在这项工作中,我们开发了一种独特的、自然主义的运动刺激,并使用它来探测 MST 神经元的复杂选择性。然后,将得到的数据用于估计每个神经元的前馈输入的特性。该分析得到的模型成功地解释了大部分观察到的刺激选择性,前提是输入是通过非线性积分机制组合的,该机制近似于 MST 输入之间的乘法交互。在模拟中,我们发现这种类型的整合具有提高对运动物体 3D 速度估计的功能作用。由于这种计算对于检测复杂的刺激特征具有普遍的效用,因此我们认为它可能代表分层感觉处理的一个基本方面。