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

被引：136

作者：

Billeh, Yazan N. ^{[1
]}

Cai, Binghuang ^{[1
]}

Gratiy, Sergey L. ^{[1
]}

Dai, Kael ^{[1
]}

Iyer, Ramakrishnan ^{[1
]}

Gouwens, Nathan W. ^{[1
]}

Abbasi-Asl, Reza ^{[1
,2
]}

Jia, Xiaoxuan ^{[1
]}

Siegle, Joshua H. ^{[1
]}

Olsen, Shawn R. ^{[1
]}

Koch, Christof ^{[1
]}

Mihalas, Stefan ^{[1
]}

Arkhipov, Anton ^{[1
]}

机构：

[1] Allen Inst Brain Sci, Seattle, WA 98109 USA

[2] Univ Calif San Francisco, Dept Neurol, Weill Inst Neurosci, San Francisco, CA USA

来源：

NEURON | 2020年 / 106卷 / 03期

关键词：

LOCAL-FIELD POTENTIALS; INHIBITORY NEURONS; LAYER; 4; CANONICAL MICROCIRCUIT; GABAERGIC INTERNEURONS; CORTICAL MICROCIRCUITS; SYNAPTIC CONNECTIVITY; RESPONSE PROPERTIES; SPATIAL SUMMATION; RECEPTIVE-FIELDS;

D O I：

10.1016/j.neuron.2020.01.040

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

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 simulation of the awake mouse primary visual cortex. The model was constructed at two levels of granularity, using either biophysically detailed or point neurons. Both variants have identical network connectivity and were compared to each other and to experimental recordings of visual-driven neural activity. While tuning these networks to recapitulate experimental data, we identified 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, both spatially extended and point models perform similarly at the level of firing rate distributions for the questions we investigated. All data and models are freely available as a resource for the community.

引用

页码：388 / +

页数：34