Krekelberg Bart, Albright Thomas D
Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA.
J Neurophysiol. 2005 May;93(5):2908-21. doi: 10.1152/jn.00473.2004. Epub 2004 Dec 1.
The macaque middle temporal area (MT) is exquisitely sensitive to visual motion and there is a large amount of evidence that neural activity in MT is tightly correlated with the perception of motion. The mechanisms by which MT neurons achieve their directional selectivity, however, have received considerably less attention. We investigated the motion-energy model as a description of motion mechanisms in macaque MT. We first confirmed one of the predictions of the motion-energy model; macaques-just like humans-perceive a reversed direction of motion when a stimulus reverses contrast with every displacement (reverse-phi). This reversal of perceived direction had a clear correlate in the neural responses of MT cells, which were predictive of the monkey's behavioral decisions. Second, we investigated how multiple motion-energy components are combined. Psychophysical data have been used to argue that motion-energy components representing opposite directions are subtracted from each other. Our data show, however, that the interactions among motion-energy components are more complex. In particular, we found that the influence of a given component on the response to a stimulus consisting of multiple components depends on factors other than the response to that component alone. This suggests that there are subthreshold nonlinear interactions among multiple motion-energy components; these could take place within MT or in earlier stages of the motion network such as V1. We propose a model that captures the complexity of these component interactions by means of a competitive interaction among the components. This provides a better description of the MT responses than the subtractive motion opponency envisaged in the motion-energy model, even when the latter is combined with a gain-control mechanism. The competitive interaction extends the dynamic range of the cells and allows them to provide information on more subtle changes in motion patterns, including changes that are not purely directional.
猕猴的颞中区(MT)对视觉运动极为敏感,大量证据表明MT区的神经活动与运动感知紧密相关。然而,MT神经元实现其方向选择性的机制却很少受到关注。我们研究了运动能量模型,以此来描述猕猴MT区的运动机制。我们首先证实了运动能量模型的一个预测;猕猴——与人类一样——当刺激在每次位移时对比度反转(反向φ现象)时,会感知到运动方向的反转。这种感知方向的反转在MT细胞的神经反应中有明显的对应关系,而神经反应能够预测猴子的行为决策。其次,我们研究了多个运动能量成分是如何组合的。心理物理学数据曾被用来论证代表相反方向的运动能量成分会相互抵消。然而,我们的数据表明,运动能量成分之间的相互作用更为复杂。特别是,我们发现给定成分对由多个成分组成的刺激反应的影响,取决于除该成分自身反应之外的其他因素。这表明多个运动能量成分之间存在阈下非线性相互作用;这些相互作用可能发生在MT区内,也可能发生在运动网络的早期阶段,如V1区。我们提出了一个模型,该模型通过成分之间的竞争性相互作用来捕捉这些成分相互作用的复杂性。即使将运动能量模型与增益控制机制相结合,这种竞争性相互作用也能比运动能量模型中设想的减法运动对立性更好地描述MT区的反应。这种竞争性相互作用扩展了细胞的动态范围,并使它们能够提供有关运动模式更细微变化的信息,包括并非纯粹方向性的变化。