Are v1 simple cells optimized for visual occlusions? A comparative study.
Are v1 simple cells optimized for visual occlusions? A comparative study.
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DOI：
10.1371/journal.pcbi.1003062
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发表时间：
2013
影响因子：
4.3
通讯作者：
Lücke J
中科院分区：
文献类型：
--
作者：
Bornschein J;Henniges M;Lücke J
众所周知，初级视觉皮质中的简单细胞对边缘等低水平图像成分有反应。稀疏编码和独立分量分析(ICA)作为简单细胞编码的标准计算模型出现，因为它们将它们的感受野与视觉刺激的统计联系起来。然而，这些模型没有考虑图像统计的一个显著特征，即图像分量的遮挡。在这里，我们询问闭塞是否对简单细胞感受场的预测形状有影响。我们用比较的方法来回答这个问题，并研究了简单细胞的两种模型：标准的线性模型和闭塞模型。对于这两个模型，我们同时估计最优感受野、稀疏性和刺激噪声。除了它们的分量叠加假设外，这两个模型是相同的。我们发现这些模型预测的图像编码和接受场有很大的不同。虽然这两个模型都预测了许多类似Gabor的区域，但遮挡模型预测的编码要稀疏得多，并且有高比例的“球状”接受区。由于在实验研究中使用了反向相关，所以观察到了这种相对较新的中心-环绕类型的简单细胞响应。虽然在线性稀疏编码中可以使用稀疏性和过完备性的特定选择来获得高百分比的球状区域，但在绝大多数关于线性模型(包括所有ICA模型)的研究中没有或只有低比例的报告。同样，对于这里研究的线性模型和最佳稀疏性，只观察到很低比例的球状场。相比之下，遮挡模型强有力地推断出高比例，并能很好地匹配实验观察到的高比例的“球状”场。因此，我们的计算研究表明，“球状”区域可能是初级视觉皮质中视觉遮挡的最佳编码的证据。我们视觉世界的统计数据被遮挡所主导。我们大脑处理的几乎每一个图像都是由相互遮挡的物体、动物和植物组成的。我们的视觉皮质在进化过程中以及在我们的整个生命周期中都对这种刺激进行了优化。然而，初级视觉处理的标准计算模型没有考虑遮挡。在这项研究中，我们问视觉遮挡可能会对简单细胞的预测反应特性产生什么影响，简单细胞是图像的第一个皮质处理单位。我们的结果表明，最近观察到的标准简单细胞模型的实验和预测之间的差异可以归因于闭塞。闭塞的最显著后果是许多细胞对中心周围的刺激敏感。在实验上，由于使用了新技术(反向相关)，观察到了大量这样的细胞。如果没有遮挡，它们只能在特定的环境下获得，并且没有一项开创性的研究(稀疏编码，ICA)预测到这样的领域。相比之下，一旦考虑到闭塞，新类型的反应就会自然出现。与最近的活体实验相比，我们发现闭塞模型与在猕猴、雪貂和小鼠中观察到的中心环绕的简单细胞的高比例是一致的。
Simple cells in primary visual cortex were famously found to respond to low-level image components such as edges. Sparse coding and independent component analysis (ICA) emerged as the standard computational models for simple cell coding because they linked their receptive fields to the statistics of visual stimuli. However, a salient feature of image statistics, occlusions of image components, is not considered by these models. Here we ask if occlusions have an effect on the predicted shapes of simple cell receptive fields. We use a comparative approach to answer this question and investigate two models for simple cells: a standard linear model and an occlusive model. For both models we simultaneously estimate optimal receptive fields, sparsity and stimulus noise. The two models are identical except for their component superposition assumption. We find the image encoding and receptive fields predicted by the models to differ significantly. While both models predict many Gabor-like fields, the occlusive model predicts a much sparser encoding and high percentages of ‘globular’ receptive fields. This relatively new center-surround type of simple cell response is observed since reverse correlation is used in experimental studies. While high percentages of ‘globular’ fields can be obtained using specific choices of sparsity and overcompleteness in linear sparse coding, no or only low proportions are reported in the vast majority of studies on linear models (including all ICA models). Likewise, for the here investigated linear model and optimal sparsity, only low proportions of ‘globular’ fields are observed. In comparison, the occlusive model robustly infers high proportions and can match the experimentally observed high proportions of ‘globular’ fields well. Our computational study, therefore, suggests that ‘globular’ fields may be evidence for an optimal encoding of visual occlusions in primary visual cortex. The statistics of our visual world is dominated by occlusions. Almost every image processed by our brain consists of mutually occluding objects, animals and plants. Our visual cortex is optimized through evolution and throughout our lifespan for such stimuli. Yet, the standard computational models of primary visual processing do not consider occlusions. In this study, we ask what effects visual occlusions may have on predicted response properties of simple cells which are the first cortical processing units for images. Our results suggest that recently observed differences between experiments and predictions of the standard simple cell models can be attributed to occlusions. The most significant consequence of occlusions is the prediction of many cells sensitive to center-surround stimuli. Experimentally, large quantities of such cells are observed since new techniques (reverse correlation) are used. Without occlusions, they are only obtained for specific settings and none of the seminal studies (sparse coding, ICA) predicted such fields. In contrast, the new type of response naturally emerges as soon as occlusions are considered. In comparison with recent in vivo experiments we find that occlusive models are consistent with the high percentages of center-surround simple cells observed in macaque monkeys, ferrets and mice.
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