Modeling Temporal Structure in Classical Conditioning

Abstract

The Temporal Coding Hypothesis of Miller and colleagues [7] sug(cid:173) gests that animals integrate related temporal patterns of stimuli into single memory representations. We formalize this concept using quasi-Bayes estimation to update the parameters of a con(cid:173) strained hidden Markov model. This approach allows us to account for some surprising temporal effects in the second order condition(cid:173) ing experiments of Miller et al. [1 , 2, 3], which other models are unable to explain.

Cite

Text

Courville and Touretzky. "Modeling Temporal Structure in Classical Conditioning." Neural Information Processing Systems, 2001.

Markdown

[Courville and Touretzky. "Modeling Temporal Structure in Classical Conditioning." Neural Information Processing Systems, 2001.](https://mlanthology.org/neurips/2001/courville2001neurips-modeling/)

BibTeX

@inproceedings{courville2001neurips-modeling,
  title     = {{Modeling Temporal Structure in Classical Conditioning}},
  author    = {Courville, Aaron C. and Touretzky, David S.},
  booktitle = {Neural Information Processing Systems},
  year      = {2001},
  pages     = {3-10},
  url       = {https://mlanthology.org/neurips/2001/courville2001neurips-modeling/}
}