Saturated Reconstruction of a Volume of Neocortex

Kasthuri, N; Hayworth, KJ; Berger, DR; Schalek, RL; Conchello, JA; Knowles-Barley, S; Lee D.; Vazquez-Reina, A; Kaynig, V; Jones, TR; Roberts, M; Morgan, JL; Tapia, JC; Seung, HS; Roncal, WG; et. al.


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 nonsynaptic, 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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Título según WOS: Saturated Reconstruction of a Volume of Neocortex
Título de la Revista: CELL
Volumen: 162
Número: 3
Editorial: Cell Press
Fecha de publicación: 2015
Página de inicio: 648
Página final: 661
Idioma: English


Notas: ISI