Abstract
We assembled a semi-automated reconstruction of L2/3 mouse primary visual cortex from ∼250 × 140 × 90 μm3 of electron microscopic images, including pyramidal and non-pyramidal neurons, astrocytes, microglia, oligodendrocytes and precursors, pericytes, vasculature, nuclei, mitochondria, and synapses. Visual responses of a subset of pyramidal cells are included. The data are publicly available, along with tools for programmatic and three-dimensional interactive access. Brief vignettes illustrate the breadth of potential applications relating structure to function in cortical circuits and neuronal cell biology. Mitochondria and synapse organization are characterized as a function of path length from the soma. Pyramidal connectivity motif frequencies are predicted accurately using a configuration model of random graphs. Pyramidal cells receiving more connections from nearby cells exhibit stronger and more reliable visual responses. Sample code shows data access and analysis.
Original language | English (US) |
---|---|
Pages (from-to) | 1082-1100.e24 |
Journal | Cell |
Volume | 185 |
Issue number | 6 |
DOIs | |
State | Published - Mar 17 2022 |
All Science Journal Classification (ASJC) codes
- Biochemistry, Genetics and Molecular Biology(all)
Keywords
- mouse, cortex, 3D reconstruction, electron microscopy, calcium imaging, pyramidal cell, mitochondria, synaptic connectivity, inhibitory cell, visual cortex
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Reconstruction of neocortex : Organelles, compartments, cells, circuits, and activity. / Turner, Nicholas L.; Macrina, Thomas; Bae, J. Alexander et al.
In: Cell, Vol. 185, No. 6, 17.03.2022, p. 1082-1100.e24.Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Reconstruction of neocortex
T2 - Organelles, compartments, cells, circuits, and activity
AU - Turner, Nicholas L.
AU - Macrina, Thomas
AU - Bae, J. Alexander
AU - Yang, Runzhe
AU - Wilson, Alyssa M.
AU - Schneider-Mizell, Casey
AU - Lee, Kisuk
AU - Lu, Ran
AU - Wu, Jingpeng
AU - Bodor, Agnes L.
AU - Bleckert, Adam A.
AU - Brittain, Derrick
AU - Froudarakis, Emmanouil
AU - Dorkenwald, Sven
AU - Collman, Forrest
AU - Kemnitz, Nico
AU - Ih, Dodam
AU - Silversmith, William M.
AU - Zung, Jonathan
AU - Zlateski, Aleksandar
AU - Tartavull, Ignacio
AU - Yu, Szi chieh
AU - Popovych, Sergiy
AU - Mu, Shang
AU - Wong, William
AU - Jordan, Chris S.
AU - Castro, Manuel
AU - Buchanan, Jo Ann
AU - Bumbarger, Daniel J.
AU - Takeno, Marc
AU - Torres, Russel
AU - Mahalingam, Gayathri
AU - Elabbady, Leila
AU - Li, Yang
AU - Cobos, Erick
AU - Zhou, Pengcheng
AU - Suckow, Shelby
AU - Becker, Lynne
AU - Paninski, Liam
AU - Polleux, Franck
AU - Reimer, Jacob
AU - Tolias, Andreas S.
AU - Reid, R. Clay
AU - da Costa, Nuno Maçarico
AU - Seung, H. Sebastian
N1 - Funding Information: Research was supported by the Intelligence Advanced Research Projects Activity (IARPA) via Department of Interior/Interior Business Center (DoI/IBC) contract numbers D16PC00003 , D16PC00004 , and D16PC0005 . The U.S. Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright annotation thereon. H.S.S. acknowledges support from NIH/NINDS U19 NS104648 , NIH/NEI R01 EY027036 , NIH/NIMH U01 MH114824 , NIH/NINDS R01NS104926 , NIH/NIMH RF1MH117815 , NIH/NIMH RF1MH123400 , and the Mathers Foundation , as well as assistance from Google, Amazon, and Intel. F.P. acknowledges support from NIH/NINDS R01 NS107483 . We thank S. Koolman, M. Moore, S. Morejohn, B. Silverman, K. Willie, and R. Willie for their image analyses; G. McGrath for computer system administration; and M. Husseini and L. and J. Jackel for project administration. We are grateful to J. Maitin-Shepard for making Neuroglancer freely available. We thank R. Yuste, M. Hausser, I. Segev, M. Tsodyks, D. Chklovskii, D. Tank, C. Brody, V. Hewitt, A. Wanner, and S. Papadopoulos for helpful discussions and feedback; A. Foryciarz for preliminary mitochondria analysis; and Z. Ashwood for preliminary nucleus detection data and experiments. We thank the Allen Institute for Brain Science founder, Paul G. Allen, for his vision, encouragement, and support. Disclaimer: the views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of IARPA, DoI/IBC, or the U.S. Government. Funding Information: Research was supported by the Intelligence Advanced Research Projects Activity (IARPA) via Department of Interior/Interior Business Center (DoI/IBC) contract numbers D16PC00003, D16PC00004, and D16PC0005. The U.S. Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright annotation thereon. H.S.S. acknowledges support from NIH/NINDS U19 NS104648, NIH/NEI R01 EY027036, NIH/NIMH U01 MH114824, NIH/NINDS R01NS104926, NIH/NIMH RF1MH117815, NIH/NIMH RF1MH123400, and the Mathers Foundation, as well as assistance from Google, Amazon, and Intel. F.P. acknowledges support from NIH/NINDS R01 NS107483. We thank S. Koolman, M. Moore, S. Morejohn, B. Silverman, K. Willie, and R. Willie for their image analyses; G. McGrath for computer system administration; and M. Husseini and L. and J. Jackel for project administration. We are grateful to J. Maitin-Shepard for making Neuroglancer freely available. We thank R. Yuste, M. Hausser, I. Segev, M. Tsodyks, D. Chklovskii, D. Tank, C. Brody, V. Hewitt, A. Wanner, and S. Papadopoulos for helpful discussions and feedback; A. Foryciarz for preliminary mitochondria analysis; and Z. Ashwood for preliminary nucleus detection data and experiments. We thank the Allen Institute for Brain Science founder, Paul G. Allen, for his vision, encouragement, and support. Disclaimer: the views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of IARPA, DoI/IBC, or the U.S. Government. E.C. built the calcium imaging pipeline, and E.F. J.R. and A.S.T. performed and oversaw surgery and calcium imaging. A.L.B. A.A.B. D.B. D.J.B. J.B. and N.M.d.C. generated the EM dataset after sample preparation by J.B. M.T. and N.M.d.C. R.T. G.M. and Y.L. stitched and rough aligned block one of the EM images. D.I. and T.M. stitched and rough, coarse, and fine aligned block two of the images. T.M. coarse and fine aligned all sections. W.W. built the task manager for distributed alignment. W.M.S. wrote the software for reading and writing cloud data, initially with I.T. T.M. supervised ground truth annotations. S.P. implemented a framework for 3D convolutional net CPU inference with help from A.Z. The net for boundary detection was trained by K.L. with help from J.Z. applied by J.W. and segmented by R.L. with help from A.Z. The nets for synapses and mitochondria were trained by N.L.T. applied by J.W. and segmented by N.L.T. The net for synaptic partner assignment was trained and applied by N.L.T. S.M. trained and applied the net for nucleus detection with ground truth partly generated by L.E. and F.C. S.D. N.K. and J.Z. created the proofreading system. S.-c.Y. T.M. S.D. and A.M.W. supervised proofreading and annotation. F.C. A.L.B. N.M.d.C. S.-c.Y. S.D. A.M.W. and C.S.-M. contributed proofreading and annotations. A.M.W. manually verified nucleus detections in the volume and performed cell typing with J.B. N.M.d.C. and A.L.B. N.K. and M.C. built the front end for proofreading and annotations and generated neuron meshes with W.M.S. C.S.J. built the early data-sharing system. S.D. F.C. and C.S.-M. created the connectome versioning system. F.C. W.M.S. and C.S.-M. skeletonized cells with help from J.A.B. N.L.T. and J.W. N.K. and A.M.W. rendered example cells. A.M.W. N.L.T. and J.A.B. compiled resource statistics. C.S.-M. analyzed synapses onto inhibitory cells with input from F.C. L.E. and N.M.d.C. N.L.T. analyzed mitochondria with help from A.M.W. F.P. C.S.-M. F.C. and R.Y. T.M. and R.Y. analyzed motifs in the PyC graph with input from N.L.T. J.A.B. co-registered calcium and EM images using correspondences annotated by N.M.d.C. A.A.B. and J.R. J.A.B. extracted activity traces using the approach of P.Z. and L.P. and related them to in-degree with input from J.R. A.S.T. F.C. and N.M.d.C. F.C. created the microns-explorer website with contributions from C.S.-M. and N.M.d.C. H.S.S. N.L.T. A.M.W. J.A.B. C.S.-M. and R.Y. wrote the paper with contributions from F.C. N.K. M.T. N.M.d.C. F.P. and L.P. S.S. and L.B. managed the project at the Allen Institute. T.M. managed the reconstruction team. N.L.T. and H.S.S. managed the analysis and writing. H.S.S. R.C.R. N.M.d.C. J.R. and A.S.T. managed the multi-institution collaboration. T.M. and H.S.S. disclose financial interests in Zetta Ai LLC. J.R. and A.S.T. disclose financial interests in Vathes LLC. One or more of the authors of this paper self-identifies as living with a disability. Publisher Copyright: © 2022 Elsevier Inc.
PY - 2022/3/17
Y1 - 2022/3/17
N2 - We assembled a semi-automated reconstruction of L2/3 mouse primary visual cortex from ∼250 × 140 × 90 μm3 of electron microscopic images, including pyramidal and non-pyramidal neurons, astrocytes, microglia, oligodendrocytes and precursors, pericytes, vasculature, nuclei, mitochondria, and synapses. Visual responses of a subset of pyramidal cells are included. The data are publicly available, along with tools for programmatic and three-dimensional interactive access. Brief vignettes illustrate the breadth of potential applications relating structure to function in cortical circuits and neuronal cell biology. Mitochondria and synapse organization are characterized as a function of path length from the soma. Pyramidal connectivity motif frequencies are predicted accurately using a configuration model of random graphs. Pyramidal cells receiving more connections from nearby cells exhibit stronger and more reliable visual responses. Sample code shows data access and analysis.
AB - We assembled a semi-automated reconstruction of L2/3 mouse primary visual cortex from ∼250 × 140 × 90 μm3 of electron microscopic images, including pyramidal and non-pyramidal neurons, astrocytes, microglia, oligodendrocytes and precursors, pericytes, vasculature, nuclei, mitochondria, and synapses. Visual responses of a subset of pyramidal cells are included. The data are publicly available, along with tools for programmatic and three-dimensional interactive access. Brief vignettes illustrate the breadth of potential applications relating structure to function in cortical circuits and neuronal cell biology. Mitochondria and synapse organization are characterized as a function of path length from the soma. Pyramidal connectivity motif frequencies are predicted accurately using a configuration model of random graphs. Pyramidal cells receiving more connections from nearby cells exhibit stronger and more reliable visual responses. Sample code shows data access and analysis.
KW - mouse, cortex, 3D reconstruction, electron microscopy, calcium imaging, pyramidal cell, mitochondria, synaptic connectivity, inhibitory cell, visual cortex
UR - http://www.scopus.com/inward/record.url?scp=85126290259&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85126290259&partnerID=8YFLogxK
U2 - 10.1016/j.cell.2022.01.023
DO - 10.1016/j.cell.2022.01.023
M3 - Article
C2 - 35216674
AN - SCOPUS:85126290259
SN - 0092-8674
VL - 185
SP - 1082-1100.e24
JO - Cell
JF - Cell
IS - 6
ER -