The logic of recurrent circuits in the primary visual cortex.

The logic of recurrent circuits in the primary visual cortex.
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DOI:
10.1038/s41593-023-01510-5
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发表时间:
2024-01
影响因子:
25
通讯作者:
Adesnik, Hillel
Adesnik, Hillel
中科院分区:
医学1区
文献类型:
--
作者:
Oldenburg, Ian Anton;Hendricks, William D.;Handy, Gregory;Shamardani, Kiarash;Bounds, Hayley A.;Doiron, Brent;Adesnik, Hillel

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反复的大脑皮层活动通过提炼、放大或抑制视觉输入来塑造视觉感知。然而,控制经常性活动影响的规则仍然是个谜。我们在小鼠的视皮层中使用了集合特有的双光子光遗传学,以将重复活动的影响与外部视觉输入分离开来。我们发现,受刺激的集合和邻近神经元的空间排列和视觉特征偏好共同决定了重复活动的净效应。这些系综的光激活在所有单元中驱动30 微米以上的抑制,但在更接近类似调谐的单元中均匀地驱动激活。在非相似调谐的细胞中,紧凑、协调的集合驱动网络抑制,而扩散的、协调的集合驱动激活。计算模型表明,高度反复的局部兴奋性连接和选择性汇聚到抑制性神经元上可以解释这些效应。我们的发现揭示了一个简单的逻辑,在这个逻辑中,皮质集合的空间和特征偏好决定了它们对局部重复活动的影响。利用双光子(2P)光遗传学和计算模型,作者发现无论是基于空间的规则还是基于特征的规则都不足以描述初级视觉皮质(V1)内的细胞-细胞相互作用。相反,模型必须包括这些主轴之间的相互作用。
Recurrent cortical activity sculpts visual perception by refining, amplifying or suppressing visual input. However, the rules that govern the influence of recurrent activity remain enigmatic. We used ensemble-specific two-photon optogenetics in the mouse visual cortex to isolate the impact of recurrent activity from external visual input. We found that the spatial arrangement and the visual feature preference of the stimulated ensemble and the neighboring neurons jointly determine the net effect of recurrent activity. Photoactivation of these ensembles drives suppression in all cells beyond 30 µm but uniformly drives activation in closer similarly tuned cells. In nonsimilarly tuned cells, compact, cotuned ensembles drive net suppression, while diffuse, cotuned ensembles drive activation. Computational modeling suggests that highly local recurrent excitatory connectivity and selective convergence onto inhibitory neurons explain these effects. Our findings reveal a straightforward logic in which space and feature preference of cortical ensembles determine their impact on local recurrent activity. Using two-photon (2P) optogenetics and computational modeling, the authors find that neither space-based nor feature-based rules are sufficient to describe cell–cell interactions within the primary visual cortex (V1). Instead, models must include interactions between these cardinal axes.
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