Muir Dylan R, Molina-Luna Patricia, Roth Morgane M, Helmchen Fritjof, Kampa Björn M
Biozentrum, University of Basel, Basel, Switzerland.
Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zurich, Switzerland.
PLoS Comput Biol. 2017 Dec 14;13(12):e1005888. doi: 10.1371/journal.pcbi.1005888. eCollection 2017 Dec.
Local excitatory connections in mouse primary visual cortex (V1) are stronger and more prevalent between neurons that share similar functional response features. However, the details of how functional rules for local connectivity shape neuronal responses in V1 remain unknown. We hypothesised that complex responses to visual stimuli may arise as a consequence of rules for selective excitatory connectivity within the local network in the superficial layers of mouse V1. In mouse V1 many neurons respond to overlapping grating stimuli (plaid stimuli) with highly selective and facilitatory responses, which are not simply predicted by responses to single gratings presented alone. This complexity is surprising, since excitatory neurons in V1 are considered to be mainly tuned to single preferred orientations. Here we examined the consequences for visual processing of two alternative connectivity schemes: in the first case, local connections are aligned with visual properties inherited from feedforward input (a 'like-to-like' scheme specifically connecting neurons that share similar preferred orientations); in the second case, local connections group neurons into excitatory subnetworks that combine and amplify multiple feedforward visual properties (a 'feature binding' scheme). By comparing predictions from large scale computational models with in vivo recordings of visual representations in mouse V1, we found that responses to plaid stimuli were best explained by assuming feature binding connectivity. Unlike under the like-to-like scheme, selective amplification within feature-binding excitatory subnetworks replicated experimentally observed facilitatory responses to plaid stimuli; explained selective plaid responses not predicted by grating selectivity; and was consistent with broad anatomical selectivity observed in mouse V1. Our results show that visual feature binding can occur through local recurrent mechanisms without requiring feedforward convergence, and that such a mechanism is consistent with visual responses and cortical anatomy in mouse V1.
在小鼠初级视觉皮层（V1）中，具有相似功能反应特征的神经元之间的局部兴奋性连接更强且更普遍。然而，局部连接的功能规则如何塑造V1中神经元反应的细节仍不清楚。我们假设，对视觉刺激的复杂反应可能是小鼠V1浅层局部网络内选择性兴奋性连接规则的结果。在小鼠V1中，许多神经元对重叠的光栅刺激（方格刺激）有高度选择性和促进性反应，这些反应不能简单地由单独呈现的单个光栅的反应预测。这种复杂性令人惊讶，因为V1中的兴奋性神经元被认为主要调谐到单个偏好方向。在这里，我们研究了两种替代连接方案对视觉处理的影响：在第一种情况下，局部连接与前馈输入继承的视觉属性对齐（一种“同类相似”方案，专门连接具有相似偏好方向的神经元）；在第二种情况下，局部连接将神经元分组为兴奋性子网，这些子网组合并放大多个前馈视觉属性（一种“特征绑定”方案）。通过将大规模计算模型的预测与小鼠V1中视觉表征的体内记录进行比较，我们发现，通过假设特征绑定连接可以最好地解释对方格刺激的反应。与同类相似方案不同，特征绑定兴奋性子网内的选择性放大复制了实验观察到的对方格刺激的促进性反应；解释了光栅选择性无法预测的选择性方格反应；并且与在小鼠V1中观察到的广泛解剖学选择性一致。我们的结果表明，视觉特征绑定可以通过局部循环机制发生，而无需前馈汇聚，并且这种机制与小鼠V1中的视觉反应和皮层解剖结构一致。
