Complex Pattern Selectivity in Macaque Primary Visual Cortex Revealed by Large-Scale Two-Photon Imaging
Complex Pattern Selectivity in Macaque Primary Visual Cortex Revealed by Large-Scale Two-Photon Imaging
复制标题
大规模双光子成像揭示猕猴初级视觉皮层的复杂模式选择性
DOI：
10.1016/j.cub.2017.11.039
复制
发表时间：
2018-01-08
期刊：
影响因子：
9.2
通讯作者：
Jiang, Hongfei
中科院分区：
文献类型：
--
作者：
Tang, Shiming;Lee, Tai Sing;Jiang, Hongfei
视觉对象包含丰富的局部高阶模式，如曲率、角点和连接点。在视觉对象识别的标准层次模型中，V1神经元通常被假设为编码这些高阶模式的局部方向分量。在这里，通过在清醒的猕猴中使用双光子成像并系统地表征V1神经元对广泛的刺激的反应，我们发现V1浅层中的大部分神经元对复杂的模式（如拐角、连接和曲率）的反应比对它们的定向线或边缘组件的反应更强烈。我们的研究结果表明，这些单独的V1神经元可以发挥作用，在检测局部高阶视觉模式的早期阶段的物体识别等级。
Visual objects contain rich local high-order patterns such as curvature, corners, and junctions. In the standard hierarchical model of visual object recognition, V1 neurons were commonly assumed to code local orientation components of those high-order patterns. Here, by using two-photon imaging in awake macaques and systematically characterizing V1 neuronal responses to an extensive set of stimuli, we found a large percentage of neurons in the V1 superficial layer responded more strongly to complex patterns, such as corners, junctions, and curvature, than to their oriented line or edge components. Our results suggest that those individual V1 neurons could play the role in detecting local high-order visual patterns in the early stage of object recognition hierarchy.