Figure 5. | Automatic discovery of cell types and microcircuitry from neural connectomics

Open accessCopyright infoDownload PDF

Automatic discovery of cell types and microcircuitry from neural connectomics

Figure 5.

Affiliation details

University of California, Berkeley, United States; Northwestern University, United States; Rehabilitation Institute of Chicago, United States
Figure 5.
Download figureOpen in new tabFigure 5. Discovering cell classes in the mouse retina connectome.

Here we show the maximum a posteriori (MAP) estimate for the types in the mouse retina data. (A) Input connectivity data for 950 cells for which soma positions were known. (B) Clustered connectivity matrix; each arbitrary color corresponds to a single type and will be used to identify that type in the remainder of the plot. (C) The spatial distribution of our cell types—each cell type tessellates space. Colors correspond to those in (B). (D) Connectivity between our clusters as a function of distance—the cluster consisting primarily of retinal ganglion cells (brown nodes on the graph) exhibits the expected near and far connectivity. Conn prob: probability of connection.

DOI: http://dx.doi.org/10.7554/eLife.04250.006