4.8 Article

Circuit Models of Low-Dimensional Shared Variability in Cortical Networks

Journal

NEURON
Volume 101, Issue 2, Pages 337-+

Publisher

CELL PRESS
DOI: 10.1016/j.neuron.2018.11.034

Keywords

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Funding

  1. Swartz Foundation Fellowship [2017-7]
  2. NIH [CRCNS R01DC015139-01ZRG1, 1U19NS107613-01, R01EB026953, 1RF1MH114223-01, 4R00EY020844-03, R01 EY022930, 5T32NS7391-14, P30 EY008098]
  3. NSF [DMS-1517828, DMS-1654268, Neuronex DBI-1707400, DMS-1517082]
  4. Vannevar Bush faculty fellowship [N00014-18-1-2002]
  5. Whitehall Foundation
  6. Klingenstein-Simons Fellowship
  7. Simons Foundation
  8. Sloan Research Fellowship
  9. McKnight Scholar Award

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Trial-to-trial variability is a reflection of the circuitry and cellular physiology that make up a neuronal network. A pervasive yet puzzling feature of cortical circuits is that despite their complex wiring, population-wide shared spiking variability is low dimensional. Previous model cortical networks cannot explain this global variability, and rather assume it is from external sources. We show that if the spatial and temporal scales of inhibitory coupling match known physiology, networks of model spiking neurons internally generate low-dimensional shared variability that captures population activity recorded in vivo. Shifting spatial attention into the receptive field of visual neurons has been shown to differentially modulate shared variability within and between brain areas. A top-down modulation of inhibitory neurons in our network provides a parsimonious mechanism for this attentional modulation. Our work provides a critical link between observed cortical circuit structure and realistic shared neuronal variability and its modulation.

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