Visual and nonvisual contributions to three-dimensional heading selectivity in the medial superior temporal area
Visual and nonvisual contributions to three-dimensional heading selectivity in the medial superior temporal area
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DOI：
10.1523/jneurosci.2356-05.2006
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发表时间：
2006-01-04
影响因子：
5.3
通讯作者：
DeAngelis, GC
中科院分区：
文献类型：
--
作者：
Gu, Y;Watkins, PV;DeAngelis, GC
自我运动的鲁棒感知需要视觉运动信号与非视觉线索的整合。内侧上级颞区（MSTd）的背侧亚部的神经元可能参与了这种感觉整合，因为它们选择性地响应于全球模式的光流，以及在黑暗中的平移运动。使用虚拟现实系统，我们的特点是三维（3D）调整MSTd神经元的标题方向定义的光流单独，惯性运动单独，和一致的组合的两个线索。在255 MSTd神经元，98%表现出显着的3D标题调谐响应光流，而64%的惯性运动定义的标题是有选择性的。视觉运动和惯性运动的航向偏好可能是一致的，但往往是相反的。此外，标题选择性一致的视觉/前庭刺激通常弱于单独使用光流获得的，一致的刺激下的标题偏好占主导地位的视觉输入。因此，MSTd神经元一般不整合视觉和非视觉线索，以实现更好的标题选择性。一个简单的两层神经网络，接收以眼睛为中心的视觉输入和以头部为中心的前庭输入，再现了MSTd数据的主要特征。该网络被训练为在所有刺激条件下计算以头部为中心的参考系中的航向，使得它执行视觉信号而不是前庭信号的选择性参考系变换。网络隐藏单元和MSTd神经元之间的相似性表明，MSTd可能是感觉会聚的早期阶段，参与将光流信息转换为（以头部为中心的）参考帧，以促进与前庭信号的整合。
Robust perception of self-motion requires integration of visual motion signals with nonvisual cues. Neurons in the dorsal subdivision of the medial superior temporal area (MSTd) maybe involved in this sensory integration, because they respond selectively to global patterns of optic flow, as well as translational motion in darkness. Using a virtual-reality system, we have characterized the three-dimensional (3D) tuning of MSTd neurons to heading directions defined by optic flow alone, inertial motion alone, and congruent combinations of the two cues. Among 255 MSTd neurons, 98% exhibited significant 3D heading tuning in response to optic flow, whereas 64% were selective for heading defined by inertial motion. Heading preferences for visual and inertial motion could be aligned but were just as frequently opposite. Moreover, heading selectivity in response to congruent visual/vestibular stimulation was typically weaker than that obtained using optic flow alone, and heading preferences under congruent stimulation were dominated by the visual input. Thus, MSTd neurons generally did not integrate visual and nonvisual cues to achieve better heading selectivity. A simple two-layer neural network, which received eye-centered visual inputs and head-centered vestibular inputs, reproduced the major features of the MSTd data. The network was trained to compute heading in a head-centered reference frame under all stimulus conditions, such that it performed a selective reference-frame transformation of visual, but not vestibular, signals. The similarity between network hidden units and MSTd neurons suggests that MSTd may be an early stage of sensory convergence involved in transforming optic flow information into a (head-centered) reference frame that facilitates integration with vestibular signals.