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 PfisterJeff William Lichtman

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717 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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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

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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

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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.

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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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