How Invariant Feature Selectivity Is Achieved in Cortex.
How Invariant Feature Selectivity Is Achieved in Cortex.
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DOI：
10.3389/fnsyn.2016.00026
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发表时间：
2016
影响因子：
3.7
通讯作者：
Sharpee TO
中科院分区：
文献类型：
--
作者：
Sharpee TO
将视觉场景解析为物体对生存至关重要。然而，神经系统是如何完成这一过程的，即使是在相对较好理解的视觉系统中，也仍然是未知的。特别不清楚的是，如何将详细的外围信号表示转换为独立于对象位置的面向对象的表示，并由视觉处理的最后阶段提供。这一观点讨论了计算算法的进展，用于拟合大规模模型，使其有可能重建的基础上对自然刺激的神经反应的视觉处理的中间步骤。特别地，现在可以表征不同类型的位置不变性（例如局部（也称为相位不变性）和更全局的位置不变性）如何与非线性操作交织以允许对弯曲轮廓进行编码。中层视觉区V4中的神经元表现出对沿沿着曲线轮廓的偶数和奇数对称轮廓对的选择性。这种配对让人联想到初级视觉皮层（V1）中复杂细胞的反应特性，并表明V1信号在随后的视觉皮层区域内转换的特定方式。这些例子说明，大规模的模型适合神经对自然刺激的反应，可以提供感官处理的连续阶段的生成模型。
Parsing the visual scene into objects is paramount to survival. Yet, how this is accomplished by the nervous system remains largely unknown, even in the comparatively well understood visual system. It is especially unclear how detailed peripheral signal representations are transformed into the object-oriented representations that are independent of object position and are provided by the final stages of visual processing. This perspective discusses advances in computational algorithms for fitting large-scale models that make it possible to reconstruct the intermediate steps of visual processing based on neural responses to natural stimuli. In particular, it is now possible to characterize how different types of position invariance, such as local (also known as phase invariance) and more global, are interleaved with nonlinear operations to allow for coding of curved contours. Neurons in the mid-level visual area V4 exhibit selectivity to pairs of even- and odd-symmetric profiles along curved contours. Such pairing is reminiscent of the response properties of complex cells in the primary visual cortex (V1) and suggests specific ways in which V1 signals are transformed within subsequent visual cortical areas. These examples illustrate that large-scale models fitted to neural responses to natural stimuli can provide generative models of successive stages of sensory processing.