@article {20751,
	title = {The long road of statistical learning: past, present, and future.},
	journal = {Philosophical Transactions of the Royal Society: Biological Sciences},
	volume = {372},
	year = {2017},
	pages = {DOI:2016.0047},
	abstract = {Almost all types of learning involve, to some degree, the ability to encode regularities across time and space. Although statistical learning (SL) research initially focused on offering a viable alternative to rule-based grammars and specialized mechanisms for word learning (e.g. [1,2]), the processing of regularities embedded in sensory input extends well beyond language. SL, therefore, was taken to offer a comprehensive theory of information processing, holding the promise of advancing knowledge across various domains of cognition including visual and auditory perception, multimodal integration, motor learning, segmentation, categorization and generalization, to name a few.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5124073/?report=classic},
	url = {http://rstb.royalsocietypublishing.org/content/372/1711/20160047},
	author = {Armstrong, B.C and Frost, R. and Christiansen, M.H.}
}
