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A whole-brain monosynaptic input connectome to neuron classes in mouse visual cortex.

Authors :
Yao S
Wang Q
Hirokawa KE
Ouellette B
Ahmed R
Bomben J
Brouner K
Casal L
Caldejon S
Cho A
Dotson NI
Daigle TL
Egdorf T
Enstrom R
Gary A
Gelfand E
Gorham M
Griffin F
Gu H
Hancock N
Howard R
Kuan L
Lambert S
Lee EK
Luviano J
Mace K
Maxwell M
Mortrud MT
Naeemi M
Nayan C
Ngo NK
Nguyen T
North K
Ransford S
Ruiz A
Seid S
Swapp J
Taormina MJ
Wakeman W
Zhou T
Nicovich PR
Williford A
Potekhina L
McGraw M
Ng L
Groblewski PA
Tasic B
Mihalas S
Harris JA
Cetin A
Zeng H
Source :
Nature neuroscience [Nat Neurosci] 2023 Feb; Vol. 26 (2), pp. 350-364. Date of Electronic Publication: 2022 Dec 22.
Publication Year :
2023

Abstract

Identification of structural connections between neurons is a prerequisite to understanding brain function. Here we developed a pipeline to systematically map brain-wide monosynaptic input connections to genetically defined neuronal populations using an optimized rabies tracing system. We used mouse visual cortex as the exemplar system and revealed quantitative target-specific, layer-specific and cell-class-specific differences in its presynaptic connectomes. The retrograde connectivity indicates the presence of ventral and dorsal visual streams and further reveals topographically organized and continuously varying subnetworks mediated by different higher visual areas. The visual cortex hierarchy can be derived from intracortical feedforward and feedback pathways mediated by upper-layer and lower-layer input neurons. We also identify a new role for layer 6 neurons in mediating reciprocal interhemispheric connections. This study expands our knowledge of the visual system connectomes and demonstrates that the pipeline can be scaled up to dissect connectivity of different cell populations across the mouse brain.<br /> (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Details

Language :
English
ISSN :
1546-1726
Volume :
26
Issue :
2
Database :
MEDLINE
Journal :
Nature neuroscience
Publication Type :
Academic Journal
Accession number :
36550293
Full Text :
https://doi.org/10.1038/s41593-022-01219-x