Modality-specific and modality-independent neural representations work in concert in predictive processes during sequence learning

被引:6
|
作者
Vekony, Teodora [1 ]
Takacs, Adam [2 ,3 ]
Pedraza, Felipe [1 ,4 ]
Haesebaert, Frederic [5 ]
Tillmann, Barbara [1 ,6 ]
Mihalecz, Imola [1 ]
Phelipon, Romane [1 ]
Beste, Christian [2 ,3 ]
Nemeth, Dezso [1 ,7 ,8 ]
机构
[1] Univ Claude Bernard Lyon 1, Ctr Rech Neurosci Lyon CRNL, CNRS, INSERM,U1028 UMR5292, 95 Blvd Pinel, F-69500 Bron, France
[2] Tech Univ Dresden, Fac Med, Dept Child & Adolescent Psychiat, Cognit Neurophysiol, Fetscherstr 74, D-01307 Dresden, Germany
[3] Tech Univ Dresden, Univ Neuropsychol Ctr, Fac Med, Fetscherstr 74, D-01307 Dresden, Germany
[4] Univ Lyon 2, Univ Lyon, Lab EMC EA 3082, F-69500 Bron, France
[5] Univ Claude Bernard Lyon 1, Ctr Rech Neurosci Lyon CRNL, PSYR2 Team, CNRS,INSERM,U1028 UMR5292, 95 Blvd Pinel, F-69500 Bron, France
[6] Univ Bourgogne, CNRS, UMR5022, Lab Etud Apprentissage & Dev, F-21048 Dijon, France
[7] Eotvos Lorand Univ, Inst Psychol, Kazinczy U 23-27, H-1075 Budapest, Hungary
[8] Res Ctr Nat Sci, Inst Cognit Neurosc & Psychol, Brain Memory & Language Res Grp, H-1117 Budapest, Hungary
基金
匈牙利科学研究基金会;
关键词
electroencephalography; temporal decomposition; multivariate pattern analysis; sequence learning; statistical learning; EVENT CODING TEC; FUNCTIONAL CONNECTIVITY; ERP COMPONENTS; DECOMPOSITION; PERCEPTION; IMPLICIT; DYNAMICS; EEG; RESOLUTION; FRAMEWORK;
D O I
10.1093/cercor/bhad079
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Probabilistic sequence learning supports the development of skills and enables predictive processing. It remains contentious whether visuomotor sequence learning is driven by the representation of the visual sequence (perceptual coding) or by the representation of the response sequence (motor coding). Neurotypical adults performed a visuomotor sequence learning task. Learning occurred incidentally as it was evidenced by faster responses to high-probability than to low-probability targets. To uncover the neurophysiology of the learning process, we conducted both univariate analyses and multivariate pattern analyses (MVPAs) on the temporally decomposed EEG signal. Univariate analyses showed that sequence learning modulated the amplitudes of the motor code of the decomposed signal but not in the perceptual and perceptual-motor signals. However, MVPA revealed that all 3 codes of the decomposed EEG contribute to the neurophysiological representation of the learnt probabilities. Source localization revealed the involvement of a wider network of frontal and parietal activations that were distinctive across coding levels. These findings suggest that perceptual and motor coding both contribute to the learning of sequential regularities rather than to a neither-nor distinction. Moreover, modality-specific encoding worked in concert with modality-independent representations, which suggests that probabilistic sequence learning is nonunitary and encompasses a set of encoding principles.
引用
收藏
页码:7783 / 7796
页数:14
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