Modeling implicit learning in a cross-modal audio-visual serial reaction time task

doi:10.1016/j.cogsys.2018.10.002

	Modeling implicit learning in a cross-modal audio-visual serial reaction time task
	Taesler, Philipp 1; Jablonowski, Julia 1; Fu, Qiufang2 ; Rose, Michael 1
通讯作者	Taesler, Philipp(p.taesler@uke.de)
摘要	This study examined implicit learning in a cross-modal condition, where visual and auditory stimuli were presented in an alternating fashion. Each cross-modal transition occurred with a probability of 0.85, enabling participants to gain a reaction time benefit by learning the cross-modal predictive information between colors and tones. Motor responses were randomly remapped to ensure that pure perceptual learning took place. The effect for the implicit learning was extracted from the data by fitting five different models to the data, which was highly variable due to motor variability. To examine individual learning rates for stimulus types of different discriminability and modality, the models were fitted per stimulus type and individually for each participant. The model selection identified the model that included motor variability, surprise effects for deviants and a serial position for effect onset as the most explanatory (Akaike weight 0.87). Further, there was a significant global cross-modal implicit learning effect for predictable versus deviant transitions (40 ms reaction time difference, p < 0.004). The learning rates over time differed for both modality and the stimuli within modalities, although there was no correlation to global error rates or reaction time differences between the stimulus types. These results demonstrate a modeling method that is well suited to extract detailed information about the success of implicit learning from high variability data. It further shows a cross-modal implicit learning effect, which extends the understanding of the implicit learning system and highlights the possibility for information to be processed in a cross-modal representation without conscious processing. (C) 2018 Elsevier B.V. All rights reserved.
关键词	Implicit learning Cross-modal Modeling Serial reaction time task Audio-visual
	2019-05-01
语种	英语
DOI	10.1016/j.cogsys.2018.10.002
发表期刊	COGNITIVE SYSTEMS RESEARCH
ISSN	1389-0417
卷号	54 页码:154-164
收录类别	SCI
资助项目	German Research Foundation DFG Crossmodal Learning: Adaptivity, Prediction and Interaction[TRR 169] ; German Research Foundation DFG Crossmodal Learning: Adaptivity, Prediction and Interaction[TRR 169]
出版者	ELSEVIER SCIENCE BV
WOS关键词	MECHANISMS ; SEQUENCES ; SELECTION ; EXPLICIT
WOS研究方向	Computer Science ; Neurosciences & Neurology ; Psychology
WOS类目	Computer Science, Artificial Intelligence ; Neurosciences ; Psychology, Experimental
WOS记录号	WOS:000455740800012
资助机构	German Research Foundation DFG Crossmodal Learning: Adaptivity, Prediction and Interaction
引用统计	被引频次：10[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.psych.ac.cn/handle/311026/27768
专题	脑与认知科学国家重点实验室
通讯作者	Taesler, Philipp
作者单位	1.Univ Med Ctr Hamburg Eppendorf, Inst Syst Neurosci, Martinistr 52,Bldg W34,320b, Hamburg, Germany 2.Chinese Acad Sci, Inst Psychol, State Key Lab Brain & Cognit Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Taesler, Philipp,Jablonowski, Julia,Fu, Qiufang,et al. Modeling implicit learning in a cross-modal audio-visual serial reaction time task[J]. COGNITIVE SYSTEMS RESEARCH,2019,54:154-164.
APA	Taesler, Philipp,Jablonowski, Julia,Fu, Qiufang,&Rose, Michael.(2019).Modeling implicit learning in a cross-modal audio-visual serial reaction time task.COGNITIVE SYSTEMS RESEARCH,54,154-164.
MLA	Taesler, Philipp,et al."Modeling implicit learning in a cross-modal audio-visual serial reaction time task".COGNITIVE SYSTEMS RESEARCH 54(2019):154-164.

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