多区域神经像素记录揭示了子网络介导前馈和反馈过程

Xiaoxuan Jia, J. Siegle, Yazan N. Billeh, S. Durand, Greggory Heller, Tamina Ramirez, A. Arkhipov, Shawn R. Olsen
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引用次数: 0

摘要

视觉系统是由前馈和反馈通路介导的跨区域通信分层组织的。然而,从功能上分离这些连接是具有挑战性的,因此信息流的逻辑仍然不清楚。在这里,我们通过使用Neuropixels探针同时记录清醒小鼠的六个视觉皮质区域来研究这个问题。我们根据其功能连接模式发现了两个不同的神经集成:一个集成由驱动网络活动的连接主导(“驱动”),而另一个集成更多地由网络活动驱动(“驱动”)。“驱动”神经元在颗粒上层更多,而“驱动”神经元在颗粒内层更丰富。有趣的是,尽管“驱动”和“被驱动”神经元在所有皮层区域都被发现,但在视觉层次上,“驱动到驱动”细胞的比例系统地增加了。在感觉刺激期间,这些子网络之间存在强烈的定向信息流,但在自发活动期间则不存在。与“被驱动”集成相比,“驱动”集成显示出更早且更多的瞬态响应。网络的速率模型概括了响应延迟和功能连接之间的联系。总体而言,我们的研究揭示了不同的多区域集成在信息流中具有不同的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Subnetworks mediating feedforward and feedback processes revealed by multi-area Neuropixels recordings
The visual system is organized hierarchically with feedforward and feedback pathways mediating crossarea communication. However, it is challenging to segregate these connections functionally and thus the logic of information flow remains unclear. Here, we studied this question by simultaneously recording from six visual cortical areas in awake mice with Neuropixels probes. We found two distinct neural ensembles based on their functional connectivity pattern: one ensemble is dominated by connections that drive the activity in the network (‘driver’), while another ensemble is more driven by network activity (‘driven’). ‘Driver’ neurons were more numerous in supragranular layers, whereas ‘driven’ neurons were more abundant in infragranular layers. Interestingly, although both ‘driver’ and ‘driven’ neurons were found across all cortical areas, the proportion of driven-to-driver cells systematically increased across the visual hierarchy. Strong directional information flow between these subnetworks was present during sensory stimulation, but not during spontaneous activity. The ‘driver’ ensemble showed earlier and more transient responses compared to the ‘driven’ ensemble. A rate model of the network recapitulated the link between response latency and functional connectivity. Overall, our study revealed distinct multi-area ensembles with distinct roles in information flow.
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