State-dependent spiking neuronal network characterization using Granger Causality based generalized linear models

  • Takahashi, Kazutaka (University of Chicago)
  • Pesce, Lorenzo
  • Iriarte-Diaz, Jose
  • Hatsopoulos, Nicholas
  • Callum, Ross
  • Sanggyun, Kim (UC San Diego)
  • Coleman, Todd

Although most of movements are kinematically smooth, they can be decomposed into multiple either behavioral or kinematic states. However, how cortical network change according to those states have not been well established. In this study, we apply a notion of Granger causality to a point process model of spiking neurons to estimate functional connectivity among spiking neurons recorded simultaneously from an Utah array implanted in the primary motor cortex, and investigated how Granger causally related network of neurons change their topology based on various behavioral or kinematically defined states, and how such changes in network can be related to dynamics of local field potentials.

Last-modified: 2012-12-18 (火) 15:56:32