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Visual physiology of the layer 4 cortical circuit in silico.
Arkhipov, Anton; Gouwens, Nathan W; Billeh, Yazan N; Gratiy, Sergey; Iyer, Ramakrishnan; Wei, Ziqiang; Xu, Zihao; Abbasi-Asl, Reza; Berg, Jim; Buice, Michael; Cain, Nicholas; da Costa, Nuno; de Vries, Saskia; Denman, Daniel; Durand, Severine; Feng, David; Jarsky, Tim; Lecoq, Jérôme; Lee, Brian; Li, Lu; Mihalas, Stefan; Ocker, Gabriel K; Olsen, Shawn R; Reid, R Clay; Soler-Llavina, Gilberto; Sorensen, Staci A; Wang, Quanxin; Waters, Jack; Scanziani, Massimo; Koch, Christof.
Afiliación
  • Arkhipov A; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Gouwens NW; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Billeh YN; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Gratiy S; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Iyer R; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Wei Z; Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America.
  • Xu Z; University of California San Diego, La Jolla, CA, United States of America.
  • Abbasi-Asl R; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Berg J; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Buice M; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Cain N; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • da Costa N; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • de Vries S; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Denman D; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Durand S; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Feng D; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Jarsky T; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Lecoq J; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Lee B; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Li L; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Mihalas S; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Ocker GK; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Olsen SR; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Reid RC; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Soler-Llavina G; Novartis Institutes for BioMedical Research, Cambridge, MA, United States of America.
  • Sorensen SA; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Wang Q; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Waters J; Allen Institute for Brain Science, Seattle, Washington, United States of America.
  • Scanziani M; Howard Hughes Medical Institute and Department of Physiology, University of California San Francisco, San Francisco, California, United States of America.
  • Koch C; Allen Institute for Brain Science, Seattle, Washington, United States of America.
PLoS Comput Biol ; 14(11): e1006535, 2018 11.
Article en En | MEDLINE | ID: mdl-30419013
ABSTRACT
Despite advances in experimental techniques and accumulation of large datasets concerning the composition and properties of the cortex, quantitative modeling of cortical circuits under in-vivo-like conditions remains challenging. Here we report and publicly release a biophysically detailed circuit model of layer 4 in the mouse primary visual cortex, receiving thalamo-cortical visual inputs. The 45,000-neuron model was subjected to a battery of visual stimuli, and results were compared to published work and new in vivo experiments. Simulations reproduced a variety of observations, including effects of optogenetic perturbations. Critical to the agreement between responses in silico and in vivo were the rules of functional synaptic connectivity between neurons. Interestingly, after extreme simplification the model still performed satisfactorily on many measurements, although quantitative agreement with experiments suffered. These results emphasize the importance of functional rules of cortical wiring and enable a next generation of data-driven models of in vivo neural activity and computations.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Corteza Visual Límite: Animals Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Corteza Visual Límite: Animals Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos