Inhibitory specificity from a connectomic census of mouse visual cortex
Mammalian cortex features a vast diversity of neuronal cell types, each with characteristic anatomical, molecular and functional properties<sup>1</sup>. Synaptic connectivity shapes how each cell type participates in the cortical circuit, but mapping connectivity rules at the resolution of distinct cell types remains difficult. Here we used millimetre-scale volumetric electron microscopy<sup>2</sup> to investigate the connectivity of all inhibitory neurons across a densely segmented neuronal population of 1,352 cells spanning all layers of mouse visual cortex, producing a wiring diagram of inhibition with more than 70,000 synapses. Inspired by classical neuroanatomy, we classified inhibitory neurons based on targeting of dendritic compartments and developed an excitatory neuron classification based on dendritic reconstructions with whole-cell maps of synaptic input. Single-cell connectivity showed a class of disinhibitory specialist that targets basket cells. Analysis of inhibitory connectivity onto excitatory neurons found widespread specificity, with many interneurons exhibiting differential targeting of spatially intermingled subpopulations. Inhibitory targeting was organized into 'motif groups', diverse sets of cells that collectively target both perisomatic and dendritic compartments of the same excitatory targets. Collectively, our analysis identified new organizing principles for cortical inhibition and will serve as a foundation for linking contemporary multimodal neuronal atlases with the cortical wiring diagram.
Authors
- Ágnes L. Bodor (ORCID: https://orcid.org/0000-0003-2082-9935)
- R. Clay Reid (ORCID: https://orcid.org/0000-0002-8697-6797)
- Manuel Castro (ORCID: https://orcid.org/0000-0003-2787-0332)
- Sergiy Popovych (ORCID: https://orcid.org/0000-0002-6158-9782)
- JoAnn Buchanan (ORCID: https://orcid.org/0000-0002-4212-5560)
- Clare Gamlin (ORCID: https://orcid.org/0000-0002-5975-7003)
- Nuno Maçarico da Costa (ORCID: https://orcid.org/0000-0003-2001-4568)
- Thomas Macrina (ORCID: https://orcid.org/0000-0002-0622-9338)
- Russel Torres (ORCID: https://orcid.org/0000-0002-2876-4382)
- Sven Dorkenwald (ORCID: https://orcid.org/0000-0003-2352-319X)
- Shanka Subhra Mondal (ORCID: https://orcid.org/0000-0003-1252-0129)
- Leila Elabbady (ORCID: https://orcid.org/0000-0002-1452-1603)
- Ran Lu (ORCID: https://orcid.org/0000-0002-2077-8165)
- Shelby Suckow
- Nicholas L. Turner (ORCID: https://orcid.org/0000-0001-5382-3420)
- H. Sebastian Seung (ORCID: https://orcid.org/0000-0002-8591-6733)
- William Silversmith (ORCID: https://orcid.org/0000-0002-5485-5341)
- Nico Kemnitz (ORCID: https://orcid.org/0000-0002-0260-4532)
- Jingpeng Wu (ORCID: https://orcid.org/0000-0003-1604-8802)
- Sam Kinn (ORCID: https://orcid.org/0000-0003-1951-8224)
- Marc Takeno (ORCID: https://orcid.org/0000-0002-8384-7500)
- Daniel J. Bumbarger (ORCID: https://orcid.org/0000-0001-6224-1633)
- Andreas S. Tolias (ORCID: https://orcid.org/0000-0002-4305-6376)
- Shang Mu (ORCID: https://orcid.org/0000-0003-0393-467X)
- Akhilesh Halageri (ORCID: https://orcid.org/0000-0001-7367-4776)
- Jacob Reimer (ORCID: https://orcid.org/0000-0003-4364-8846)
- Casey M Schneider-Mizell (ORCID: https://orcid.org/0000-0001-9477-3853)
- Eric Mitchell (ORCID: https://orcid.org/0000-0002-7487-1744)
- Gayathri Mahalingam (ORCID: https://orcid.org/0000-0003-3718-5013)
- Sharmishtaa Seshamani (ORCID: https://orcid.org/0000-0001-7289-3184)
- Forrest Collman (ORCID: https://orcid.org/0000-0002-0280-7022)
- Barak Nehoran (ORCID: https://orcid.org/0000-0001-7371-0829)
- Derrick Brittain (ORCID: https://orcid.org/0000-0003-3890-2862)
- Daniel Kapner
- Kai Li (ORCID: https://orcid.org/0000-0002-2095-7024)
- J. Alexander Bae (ORCID: https://orcid.org/0000-0002-4681-6342)
- Wenjing Yin (ORCID: https://orcid.org/0000-0003-1932-5561)
- Kisuk Lee (ORCID: https://orcid.org/0000-0001-5707-0155)
- Zhen Jia (ORCID: https://orcid.org/0000-0003-3543-2324)
- William Wong
- Chris Jordan
Institutions
- Allen Institute for Brain Science (US)
- Baylor College of Medicine (US)
- Princeton University (US)
- Allen Institute (US)
- Massachusetts Institute of Technology (US)
- Rice University (US)
Publication Details
- Journal
- Nature
- Published
- 2025-04-09
- DOI
- https://doi.org/10.1038/s41586-024-07780-8
- Citations
- 52
- Primary Topic
- Neural dynamics and brain function
- Type
- article
- Field-Weighted Citation Impact
- 71.56