Saturated Reconstruction of a Volume of Neocortex

Narayanan Kasthuri; Kenneth Jeffrey Hayworth; Daniel Raimund Berger; Richard Lee Schalek; José Angel Conchello; Seymour Knowles-Barley; Dongil Lee; Amelio Vázquez-Reina; Verena Kaynig; Thouis Raymond Jones; Mike Roberts; Josh Lyskowski Morgan; Juan Carlos Tapia; H. Sebastian Seung; William Gray Roncal; Joshua Tzvi Vogelstein; Randal Burns; Daniel Lewis Sussman; Carey Eldin Priebe; Hanspeter Pfister; Jeff William Lichtman

doi:10.1016/j.cell.2015.06.054

Saturated Reconstruction of a Volume of Neocortex

Narayanan Kasthuri
, Kenneth Jeffrey Hayworth
, Daniel Raimund Berger
, Richard Lee Schalek
, José Angel Conchello
, Seymour Knowles-Barley
, Dongil Lee
, Amelio Vázquez-Reina
, Verena Kaynig
, Thouis Raymond Jones
, Mike Roberts
, Josh Lyskowski Morgan
, Juan Carlos Tapia
, H. Sebastian Seung
, William Gray Roncal
, Joshua Tzvi Vogelstein
, Randal Burns
, Daniel Lewis Sussman
, Carey Eldin Priebe
, Hanspeter Pfister

Jeff William Lichtman

Research output: Contribution to journal › Article › peer-review

775 Scopus citations

Abstract

We describe automated technologies to probe the structure of neural tissue at nanometer resolution and use them to generate a saturated reconstruction of a sub-volume of mouse neocortex in which all cellular objects (axons, dendrites, and glia) and many sub-cellular components (synapses, synaptic vesicles, spines, spine apparati, postsynaptic densities, and mitochondria) are rendered and itemized in a database. We explore these data to study physical properties of brain tissue. For example, by tracing the trajectories of all excitatory axons and noting their juxtapositions, both synaptic and non-synaptic, with every dendritic spine we refute the idea that physical proximity is sufficient to predict synaptic connectivity (the so-called Peters' rule). This online minable database provides general access to the intrinsic complexity of the neocortex and enables further data-driven inquiries.

Original language	English
Pages (from-to)	648-661
Number of pages	14
Journal	Cell
Volume	162
Issue number	3
DOIs	https://doi.org/10.1016/j.cell.2015.06.054
State	Published - Aug 1 2015

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10.1016/j.cell.2015.06.054

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Kasthuri, N., Hayworth, K. J., Berger, D. R., Schalek, R. L., Conchello, J. A., Knowles-Barley, S., Lee, D., Vázquez-Reina, A., Kaynig, V., Jones, T. R., Roberts, M., Morgan, J. L., Tapia, J. C., Seung, H. S., Roncal, W. G., Vogelstein, J. T., Burns, R., Sussman, D. L., Priebe, C. E., ... Lichtman, J. W. (2015). Saturated Reconstruction of a Volume of Neocortex. Cell, 162(3), 648-661. https://doi.org/10.1016/j.cell.2015.06.054

@article{a4ca25e2025a42849f42c4de0eb2f703,

title = "Saturated Reconstruction of a Volume of Neocortex",

abstract = "We describe automated technologies to probe the structure of neural tissue at nanometer resolution and use them to generate a saturated reconstruction of a sub-volume of mouse neocortex in which all cellular objects (axons, dendrites, and glia) and many sub-cellular components (synapses, synaptic vesicles, spines, spine apparati, postsynaptic densities, and mitochondria) are rendered and itemized in a database. We explore these data to study physical properties of brain tissue. For example, by tracing the trajectories of all excitatory axons and noting their juxtapositions, both synaptic and non-synaptic, with every dendritic spine we refute the idea that physical proximity is sufficient to predict synaptic connectivity (the so-called Peters' rule). This online minable database provides general access to the intrinsic complexity of the neocortex and enables further data-driven inquiries.",

author = "Narayanan Kasthuri and Hayworth, \{Kenneth Jeffrey\} and Berger, \{Daniel Raimund\} and Schalek, \{Richard Lee\} and Conchello, \{Jos{\'e} Angel\} and Seymour Knowles-Barley and Dongil Lee and Amelio V{\'a}zquez-Reina and Verena Kaynig and Jones, \{Thouis Raymond\} and Mike Roberts and Morgan, \{Josh Lyskowski\} and Tapia, \{Juan Carlos\} and Seung, \{H. Sebastian\} and Roncal, \{William Gray\} and Vogelstein, \{Joshua Tzvi\} and Randal Burns and Sussman, \{Daniel Lewis\} and Priebe, \{Carey Eldin\} and Hanspeter Pfister and Lichtman, \{Jeff William\}",

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year = "2015",

month = aug,

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doi = "10.1016/j.cell.2015.06.054",

language = "English",

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Kasthuri, N, Hayworth, KJ, Berger, DR, Schalek, RL, Conchello, JA, Knowles-Barley, S, Lee, D, Vázquez-Reina, A, Kaynig, V, Jones, TR, Roberts, M, Morgan, JL, Tapia, JC, Seung, HS, Roncal, WG, Vogelstein, JT, Burns, R, Sussman, DL, Priebe, CE, Pfister, H & Lichtman, JW 2015, 'Saturated Reconstruction of a Volume of Neocortex', Cell, vol. 162, no. 3, pp. 648-661. https://doi.org/10.1016/j.cell.2015.06.054

TY - JOUR

T1 - Saturated Reconstruction of a Volume of Neocortex

AU - Kasthuri, Narayanan

AU - Hayworth, Kenneth Jeffrey

AU - Berger, Daniel Raimund

AU - Schalek, Richard Lee

AU - Conchello, José Angel

AU - Knowles-Barley, Seymour

AU - Lee, Dongil

AU - Vázquez-Reina, Amelio

AU - Kaynig, Verena

AU - Jones, Thouis Raymond

AU - Roberts, Mike

AU - Morgan, Josh Lyskowski

AU - Tapia, Juan Carlos

AU - Seung, H. Sebastian

AU - Roncal, William Gray

AU - Vogelstein, Joshua Tzvi

AU - Burns, Randal

AU - Sussman, Daniel Lewis

AU - Priebe, Carey Eldin

AU - Pfister, Hanspeter

AU - Lichtman, Jeff William

PY - 2015/8/1

Y1 - 2015/8/1

N2 - We describe automated technologies to probe the structure of neural tissue at nanometer resolution and use them to generate a saturated reconstruction of a sub-volume of mouse neocortex in which all cellular objects (axons, dendrites, and glia) and many sub-cellular components (synapses, synaptic vesicles, spines, spine apparati, postsynaptic densities, and mitochondria) are rendered and itemized in a database. We explore these data to study physical properties of brain tissue. For example, by tracing the trajectories of all excitatory axons and noting their juxtapositions, both synaptic and non-synaptic, with every dendritic spine we refute the idea that physical proximity is sufficient to predict synaptic connectivity (the so-called Peters' rule). This online minable database provides general access to the intrinsic complexity of the neocortex and enables further data-driven inquiries.

AB - We describe automated technologies to probe the structure of neural tissue at nanometer resolution and use them to generate a saturated reconstruction of a sub-volume of mouse neocortex in which all cellular objects (axons, dendrites, and glia) and many sub-cellular components (synapses, synaptic vesicles, spines, spine apparati, postsynaptic densities, and mitochondria) are rendered and itemized in a database. We explore these data to study physical properties of brain tissue. For example, by tracing the trajectories of all excitatory axons and noting their juxtapositions, both synaptic and non-synaptic, with every dendritic spine we refute the idea that physical proximity is sufficient to predict synaptic connectivity (the so-called Peters' rule). This online minable database provides general access to the intrinsic complexity of the neocortex and enables further data-driven inquiries.

UR - https://www.scopus.com/pages/publications/84938233335

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DO - 10.1016/j.cell.2015.06.054

M3 - Article

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AN - SCOPUS:84938233335

SN - 0092-8674

VL - 162

SP - 648

EP - 661

JO - Cell

JF - Cell

IS - 3

ER -

Saturated Reconstruction of a Volume of Neocortex

Abstract

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