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    Rights statement: This is the peer reviewed version of the following article:Rebuschat, P. and Monaghan, P. (2019), Editors’ Introduction: Aligning Implicit Learning and Statistical Learning: Two Approaches, One Phenomenon. Top Cogn Sci, 11: 459-467. doi:10.1111/tops.12438 which has been published in final form at https://onlinelibrary.wiley.com/doi/full/10.1111/tops.12438 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

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Editors' introduction: Aligning implicit learning and statistical learning: Two approaches, one phenomenon

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Editors' introduction: Aligning implicit learning and statistical learning: Two approaches, one phenomenon. / Rebuschat, Patrick; Monaghan, Padraic.
In: Topics in Cognitive Science, Vol. 11, No. 3, 23.07.2019, p. 459-467.

Research output: Contribution to Journal/MagazineEditorialpeer-review

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@article{f3341be330854e748ad6a1f2874557be,
title = "Editors' introduction: Aligning implicit learning and statistical learning: Two approaches, one phenomenon",
abstract = "In their editors{\textquoteright} introduction, Rebuschat and Monaghan provide the background to the special issue. They outline the rationale for bringing together, in a single volume, leading researchers from two distinct, yet related research strands,implicit learning and statistical learning. The editors then introduce the new contributions solicited for this special issueand provide their perspective on the agenda setting that results from combining these two approaches.",
author = "Patrick Rebuschat and Padraic Monaghan",
note = "This is the peer reviewed version of the following article:Rebuschat, P. and Monaghan, P. (2019), Editors{\textquoteright} Introduction: Aligning Implicit Learning and Statistical Learning: Two Approaches, One Phenomenon. Top Cogn Sci, 11: 459-467. doi:10.1111/tops.12438 which has been published in final form at https://onlinelibrary.wiley.com/doi/full/10.1111/tops.12438 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.",
year = "2019",
month = jul,
day = "23",
doi = "10.1111/tops.12438",
language = "English",
volume = "11",
pages = "459--467",
journal = "Topics in Cognitive Science",
issn = "1756-8757",
publisher = "Blackwell-Wiley",
number = "3",

}

RIS

TY - JOUR

T1 - Editors' introduction: Aligning implicit learning and statistical learning: Two approaches, one phenomenon

AU - Rebuschat, Patrick

AU - Monaghan, Padraic

N1 - This is the peer reviewed version of the following article:Rebuschat, P. and Monaghan, P. (2019), Editors’ Introduction: Aligning Implicit Learning and Statistical Learning: Two Approaches, One Phenomenon. Top Cogn Sci, 11: 459-467. doi:10.1111/tops.12438 which has been published in final form at https://onlinelibrary.wiley.com/doi/full/10.1111/tops.12438 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

PY - 2019/7/23

Y1 - 2019/7/23

N2 - In their editors’ introduction, Rebuschat and Monaghan provide the background to the special issue. They outline the rationale for bringing together, in a single volume, leading researchers from two distinct, yet related research strands,implicit learning and statistical learning. The editors then introduce the new contributions solicited for this special issueand provide their perspective on the agenda setting that results from combining these two approaches.

AB - In their editors’ introduction, Rebuschat and Monaghan provide the background to the special issue. They outline the rationale for bringing together, in a single volume, leading researchers from two distinct, yet related research strands,implicit learning and statistical learning. The editors then introduce the new contributions solicited for this special issueand provide their perspective on the agenda setting that results from combining these two approaches.

U2 - 10.1111/tops.12438

DO - 10.1111/tops.12438

M3 - Editorial

VL - 11

SP - 459

EP - 467

JO - Topics in Cognitive Science

JF - Topics in Cognitive Science

SN - 1756-8757

IS - 3

ER -