• Corpus ID: 5648277

Building a Dynamical Network Model from Neural Spiking Data: Application of Poisson Likelihood

@article{Doruk2017BuildingAD,
  title={Building a Dynamical Network Model from Neural Spiking Data: Application of Poisson Likelihood},
  author={Ozgur R Doruk and Kechen Zhang},
  journal={arXiv: Neurons and Cognition},
  year={2017}
}
Research showed that, the information transmitted in biological neurons is encoded in the instants of successive action potentials or their firing rate. In addition to that, in-vivo operation of the neuron makes measurement difficult and thus continuous data collection is restricted. Due to those reasons, classical mean square estimation techniques that are frequently used in neural network training is very difficult to apply. In such situations, point processes and related likelihood methods… 

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