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Systematic Integration of Structural and Functional Data into Multi-Scale Models of Mouse Primary Visual Cortex

View ORCID ProfileYazan N. Billeh, Binghuang Cai, Sergey L. Gratiy, Kael Dai, Ramakrishnan Iyer, Nathan W. Gouwens, Reza Abbasi-Asl, Xiaoxuan Jia, Joshua H. Siegle, Shawn R. Olsen, Christof Koch, Stefan Mihalas, Anton Arkhipov
doi: https://doi.org/10.1101/662189
Yazan N. Billeh
1Allen Institute for Brain Science, Seattle, WA
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  • For correspondence: yazanb@alleninstitute.org antona@alleninstitute.org
Binghuang Cai
1Allen Institute for Brain Science, Seattle, WA
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Sergey L. Gratiy
1Allen Institute for Brain Science, Seattle, WA
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Kael Dai
1Allen Institute for Brain Science, Seattle, WA
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Ramakrishnan Iyer
1Allen Institute for Brain Science, Seattle, WA
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Nathan W. Gouwens
1Allen Institute for Brain Science, Seattle, WA
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Reza Abbasi-Asl
1Allen Institute for Brain Science, Seattle, WA
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Xiaoxuan Jia
1Allen Institute for Brain Science, Seattle, WA
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Joshua H. Siegle
1Allen Institute for Brain Science, Seattle, WA
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Shawn R. Olsen
1Allen Institute for Brain Science, Seattle, WA
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Christof Koch
1Allen Institute for Brain Science, Seattle, WA
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Stefan Mihalas
1Allen Institute for Brain Science, Seattle, WA
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Anton Arkhipov
1Allen Institute for Brain Science, Seattle, WA
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  • For correspondence: yazanb@alleninstitute.org antona@alleninstitute.org
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Abstract

Structural rules underlying functional properties of cortical circuits are poorly understood. To explore these rules systematically, we integrated information from extensive literature curation and large-scale experimental surveys into a data-driven, biologically realistic model of the mouse primary visual cortex. The model was constructed at two levels of granularity, using either biophysically-detailed or point-neurons, with identical network connectivity. Both variants were compared to each other and to experimental recordings of neural activity during presentation of visual stimuli to awake mice. While constructing and tuning these networks to recapitulate experimental data, we identified a set of rules governing cell-class specific connectivity and synaptic strengths. These structural constraints constitute hypotheses that can be tested experimentally. Despite their distinct single cell abstraction, spatially extended or point-models, both perform similarly at the level of firing rate distributions. All data and models are freely available as a resource for the community.

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  • ↵2 Lead contact

  • https://brain-map.org/explore/models/mv1-all-layers

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted October 18, 2019.
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Systematic Integration of Structural and Functional Data into Multi-Scale Models of Mouse Primary Visual Cortex
Yazan N. Billeh, Binghuang Cai, Sergey L. Gratiy, Kael Dai, Ramakrishnan Iyer, Nathan W. Gouwens, Reza Abbasi-Asl, Xiaoxuan Jia, Joshua H. Siegle, Shawn R. Olsen, Christof Koch, Stefan Mihalas, Anton Arkhipov
bioRxiv 662189; doi: https://doi.org/10.1101/662189
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Systematic Integration of Structural and Functional Data into Multi-Scale Models of Mouse Primary Visual Cortex
Yazan N. Billeh, Binghuang Cai, Sergey L. Gratiy, Kael Dai, Ramakrishnan Iyer, Nathan W. Gouwens, Reza Abbasi-Asl, Xiaoxuan Jia, Joshua H. Siegle, Shawn R. Olsen, Christof Koch, Stefan Mihalas, Anton Arkhipov
bioRxiv 662189; doi: https://doi.org/10.1101/662189

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