Statistical models for neural encoding, decoding, and optimal stimulus design.

@article{Paninski2007StatisticalMF,
  title={Statistical models for neural encoding, decoding, and optimal stimulus design.},
  author={Liam Paninski and Jonathan W. Pillow and Jeremy Lewi},
  journal={Progress in brain research},
  year={2007},
  volume={165},
  pages={493-507}
}
There are two basic problems in the statistical analysis of neural data. The "encoding" problem concerns how information is encoded in neural spike trains: can we predict the spike trains of a neuron (or population of neurons), given an arbitrary stimulus or observed motor response? Conversely, the "decoding" problem concerns how much information is in a spike train, in particular, how well can we estimate the stimulus that gave rise to the spike train? This chapter describes statistical model… CONTINUE READING
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