@article {Grainger245,
	author = {Grainger, Jonathan and Dufau, St{\'e}phane and Montant, Marie and Ziegler, Johannes C. and Fagot, Jo{\"e}l},
	title = {Orthographic Processing in Baboons (Papio papio)},
	volume = {336},
	number = {6078},
	pages = {245--248},
	year = {2012},
	doi = {10.1126/science.1218152},
	publisher = {American Association for the Advancement of Science},
	abstract = {An orthographic object such as a set of letters, and the ability to recognize such sets as words, is a key component of reading. The ability to develop these skills has often been attributed to the prior acquisition of a complex language. For example, we learn how letters sound and thus recognize when a particular letter makes up part of a word. However, orthographic processing is also a visual process, because we learn to recognize words as discrete objects, and the ability to read may thus be related to an ability to recognize and classify objects. Grainger et al. (p. 245; see the Perspective by Platt and Adams) tested orthographic skills in baboons. Captive, but freely ranging, baboons were trained to distinguish real English words from combinations of similar letters that are not words, and they were able to distinguish real words with remarkable accuracy. Thus, a basic ability to recognize words as objects does not require complex linguistic understanding.Skilled readers use information about which letters are where in a word (orthographic information) in order to access the sounds and meanings of printed words. We asked whether efficient processing of orthographic information could be achieved in the absence of prior language knowledge. To do so, we trained baboons to discriminate English words from nonsense combinations of letters that resembled real words. The results revealed that the baboons were using orthographic information in order to efficiently discriminate words from letter strings that were not words. Our results demonstrate that basic orthographic processing skills can be acquired in the absence of preexisting linguistic representations.},
	issn = {0036-8075},
	URL = {http://science.sciencemag.org/content/336/6078/245},
	eprint = {http://science.sciencemag.org/content/336/6078/245.full.pdf},
	journal = {Science}
}

@Manual{Rparallel,
  title = {R: A Language and Environment for Statistical Computing},
  author = {{R Core Team}},
  organization = {R Foundation for Statistical Computing},
  address = {Vienna, Austria},
  year = {2015},
  url = {https://www.R-project.org/},
}

@Manual{Rforeach,
  title = {foreach: Provides Foreach Looping Construct for R},
  author = {Revolution Analytics and Steve Weston},
  year = {2015},
  note = {R package version 1.4.3},
  url = {https://CRAN.R-project.org/package=foreach},
}

@Manual{RdoParallel,
  title = {doParallel: Foreach Parallel Adaptor for the 'parallel' Package},
  author = {Revolution Analytics and Steve Weston},
  year = {2015},
  note = {R package version 1.0.10},
  url = {https://CRAN.R-project.org/package=doParallel},
}
@Manual{Rndl,
  title = {ndl: Naive Discriminative Learning},
  author = {{Antti Arppe} and {Peter Hendrix} and {Petar Milin} and {R. Harald Baayen} and {Cyrus Shaoul}},
  year = {2014},
  note = {R package version 0.2.16},
  url = {https://CRAN.R-project.org/package=ndl},
}
@Manual{Rcore,
  title = {R: A Language and Environment for Statistical Computing},
  author = {{R Core Team}},
  organization = {R Foundation for Statistical Computing},
  address = {Vienna, Austria},
  year = {2016},
  url = {https://www.R-project.org/},
}

@Book{Rmgcv,
  title = {Generalized Additive Models: An Introduction with R},
  year = {2006},
  author = {S.N Wood},
  publisher = {Chapman and Hall/CRC},
}
@Misc{Ritsadug,
  title = {{itsadug}: Interpreting Time Series and Autocorrelated Data Using GAMMs},
  author = {Jacolien {van Rij} and Martijn Wieling and R. Harald Baayen and Hedderik {van Rijn}},
  year = {2016},
  note = {R package version 2.0},
}
@article{baayen2015abstraction,
  title={Abstraction, storage and naive discriminative learning},
  author={Baayen, RH and Ramscar, M},
  journal={Handbook of cognitive linguistics},
  pages={99--120},
  year={2015},
  publisher={De Gruyter Mouton}
}
@article{rescorla1972theory,
  title={A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement},
  author={Rescorla, Robert A and Wagner, Allan R and others},
  journal={Classical conditioning II: Current research and theory},
  volume={2},
  pages={64--99},
  year={1972},
  publisher={New York}
}
@article{baayen2016comprehension,
  title={Comprehension without segmentation: A proof of concept with naive discriminative learning},
  author={Baayen, R Harald and Shaoul, Cyrus and Willits, Jon and Ramscar, Michael},
  journal={Language, Cognition and Neuroscience},
  volume={31},
  number={1},
  pages={106--128},
  year={2016},
  publisher={Taylor \& Francis}
}