Department of Computer Sciences, Rochester Institute of Technology Rochester, Rochester, New York, USA.
J Neurophysiol. 2010 May;103(5):2794-807. doi: 10.1152/jn.01085.2009. Epub 2010 Mar 24.
Optic flow informs moving observers about their heading direction. Neurons in monkey medial superior temporal (MST) cortex show heading selective responses to optic flow and planar direction selective responses to patches of local motion. We recorded MST neuronal responses to a 90 x 90 degrees optic flow display and to a 3 x 3 array of local motion patches covering the same area. Our goal was to test the hypothesis that the optic flow responses reflect the sum of the local motion responses. The local motion responses of each neuron were modeled as mixtures of Gaussians, combining the effects of two Gaussian response functions derived using a genetic algorithm, and then used to predict that neuron's optic flow responses. Some neurons showed good correspondence between local motion models and optic flow responses, others showed substantial differences. We used the genetic algorithm to modulate the relative strength of each local motion segment's responses to accommodate interactions between segments that might modulate their relative efficacy during co-activation by global patterns of optic flow. These gain modulated models showed uniformly better fits to the optic flow responses, suggesting that coactivation of receptive field segments alters neuronal response properties. We tested this hypothesis by simultaneously presenting local motion stimuli at two different sites. These two-segment stimuli revealed that interactions between response segments have direction and location specific effects that can account for aspects of optic flow selectivity. We conclude that MST's optic flow selectivity reflects dynamic interactions between spatially distributed local planar motion response mechanisms.
视流为运动中的观察者提供朝向信息。猴子中脑上颞(MST)皮层的神经元对视流表现出朝向选择性响应,对局部运动的斑块表现出平面方向选择性响应。我们记录了 MST 神经元对 90x90 度视流显示和覆盖相同区域的 3x3 个局部运动斑块的反应。我们的目标是检验这样一种假设,即视流响应反映了局部运动响应的总和。每个神经元的局部运动响应被建模为高斯混合,将使用遗传算法得出的两个高斯响应函数的效果结合起来,然后用于预测该神经元的视流响应。一些神经元在局部运动模型和视流响应之间表现出很好的一致性,而另一些则表现出很大的差异。我们使用遗传算法来调节每个局部运动片段响应的相对强度,以适应可能在全局视流模式共同激活期间调节它们相对效率的片段之间的相互作用。这些增益调制模型对视流响应的拟合效果更好,表明感受野片段的共同激活改变了神经元的响应特性。我们通过同时在两个不同位置呈现局部运动刺激来检验这一假设。这些两段式刺激揭示了响应片段之间的相互作用具有方向和位置特异性效应,可以解释视流选择性的某些方面。我们得出结论,MST 的视流选择性反映了空间分布的局部平面运动响应机制之间的动态相互作用。