Numerics for stochastic neural mass models

  • Harald Hinterleitner (Speaker)

Activity: Talk or presentation › Contributed talk › unknown

Description

Neural mass models provide a useful framework for modelling mesoscopic neural dynamics. We briefly introduce a generalized form of neural mass models, which turn out to be stochastic functional differential equations (SFDEs) with distributed memory terms. We solve these equations numerically with a Theta-Maruyama scheme.
Period24 Sept 2014
Event title3rd Austrian Stochastics Days
Event typeConference
LocationAustriaShow on map

Fields of science

  • 101024 Probability theory
  • 101 Mathematics
  • 101019 Stochastics
  • 101018 Statistics
  • 101014 Numerical mathematics

JKU Focus areas

  • Computation in Informatics and Mathematics
  • Engineering and Natural Sciences (in general)

Documents & Links