Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons

@article{Buesing2011NeuralDA,
  title={Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons},
  author={Lars Buesing and Johannes Bill and Bernhard Nessler and Wolfgang Maass},
  journal={PLoS Computational Biology},
  year={2011},
  volume={7}
}
The organization of computations in networks of spiking neurons in the brain is still largely unknown, in particular in view of the inherently stochastic features of their firing activity and the experimentally observed trial-to-trial variability of neural systems in the brain. In principle there exists a powerful computational framework for stochastic computations, probabilistic inference by sampling, which can explain a large number of macroscopic experimental data in neuroscience and… Expand
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