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Paper: GS-5.2
Session: Contributed Talks 9-10
Location: H0104
Session Time: Monday, September 16, 09:50 - 10:30
Presentation Time:Monday, September 16, 10:10 - 10:30
Presentation: Oral
Publication: 2019 Conference on Cognitive Computational Neuroscience, 13-16 September 2019, Berlin, Germany
Paper Title: Subnetworks mediating feedforward and feedback processes revealed by multi-area Neuropixels recordings
Manuscript:  Click here to view manuscript
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License: Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
Authors: Xiaoxuan Jia, Joshua Siegle, Yazan Billeh, Séverine Durand, Greggory Heller, Tamina Ramirez, Anton Arkhipov, Shawn Olsen, Allen Institute, United States
Abstract: The visual system is organized hierarchically with feedforward and feedback pathways mediating cross-area 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.