Connectomic reconstruction of the inner plexiform layer in the mouse retina.
Comprehensive high-resolution structural maps are central to functional exploration and understanding in biology. For the nervous system, in which high resolution and large spatial extent are both needed, such maps are scarce as they challenge data acquisition and analysis capabilities. Here we present for the mouse inner plexiform layer--the main computational neuropil region in the mammalian retina--the dense reconstruction of 950 neurons and their mutual contacts. This was achieved by applying a combination of crowd-sourced manual annotation and machine-learning-based volume segmentation to serial block-face electron microscopy data. We characterize a new type of retinal bipolar interneuron and show that we can subdivide a known type based on connectivity. Circuit motifs that emerge from our data indicate a functional mechanism for a known cellular response in a ganglion cell that detects localized motion, and predict that another ganglion cell is motion sensitive.
Max-Planck Institute for Medical Research, D-69120 Heidelberg, Germany. mhelmstaedter@neuro.mpg.de
Moritz
M
Helmstaedter
Kevin L
KL
Briggman
Srinivas C
SC
Turaga
Viren
V
Jain
H Sebastian
HS
Seung
Winfried
W
Denk
D025042:Amacrine Cells / Q000166:cytology / Q000502:physiology; D000818:Animals; D002450:Cell Communication; D063132:Connectome; D007091:Image Processing, Computer-Assisted; D051379:Mice; D008810:Mice, Inbred C57BL; D008854:Microscopy, Electron; D008954:Models, Biological; D019581:Neuropil / Q000502:physiology; D012160:Retina / Q000166:cytology* / Q000502:physiology*; D012165:Retinal Ganglion Cells / Q000166:cytology / Q000502:physiology*