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Neurophysiological and functional neuroanatomical coding of statistical and deterministic rule information during sequence learning.
Takács, Ádám; Kóbor, Andrea; Kardos, Zsófia; Janacsek, Karolina; Horváth, Kata; Beste, Christian; Nemeth, Dezso.
Afiliação
  • Takács Á; Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany.
  • Kóbor A; Brain Imaging Centre, Research Centre for Natural Sciences, Budapest, Hungary.
  • Kardos Z; Brain Imaging Centre, Research Centre for Natural Sciences, Budapest, Hungary.
  • Janacsek K; Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary.
  • Horváth K; Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary.
  • Beste C; Brain, Memory and Language Research Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary.
  • Nemeth D; Centre of Thinking and Learning, Institute for Lifecourse Development, School of Human Sciences, Faculty of Education, Health and Human Sciences, University of Greenwich, London, UK.
Hum Brain Mapp ; 42(10): 3182-3201, 2021 07.
Article em En | MEDLINE | ID: mdl-33797825
ABSTRACT
Humans are capable of acquiring multiple types of information presented in the same information stream. It has been suggested that at least two parallel learning processes are important during learning of sequential patterns-statistical learning and rule-based learning. Yet, the neurophysiological underpinnings of these parallel learning processes are not fully understood. To differentiate between the simultaneous mechanisms at the single trial level, we apply a temporal EEG signal decomposition approach together with sLORETA source localization method to delineate whether distinct statistical and rule-based learning codes can be distinguished in EEG data and can be related to distinct functional neuroanatomical structures. We demonstrate that concomitant but distinct aspects of information coded in the N2 time window play a role in these mechanisms mismatch detection and response control underlie statistical learning and rule-based learning, respectively, albeit with different levels of time-sensitivity. Moreover, the effects of the two learning mechanisms in the different temporally decomposed clusters of neural activity also differed from each other in neural sources. Importantly, the right inferior frontal cortex (BA44) was specifically implicated in visuomotor statistical learning, confirming its role in the acquisition of transitional probabilities. In contrast, visuomotor rule-based learning was associated with the prefrontal gyrus (BA6). The results show how simultaneous learning mechanisms operate at the neurophysiological level and are orchestrated by distinct prefrontal cortical areas. The current findings deepen our understanding on the mechanisms of how humans are capable of learning multiple types of information from the same stimulus stream in a parallel fashion.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizagem por Probabilidade / Aprendizagem Seriada / Potenciais Evocados / Área de Broca / Córtex Motor Tipo de estudo: Prognostic_studies Limite: Adult / Female / Humans / Male Idioma: En Revista: Hum Brain Mapp Assunto da revista: CEREBRO Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizagem por Probabilidade / Aprendizagem Seriada / Potenciais Evocados / Área de Broca / Córtex Motor Tipo de estudo: Prognostic_studies Limite: Adult / Female / Humans / Male Idioma: En Revista: Hum Brain Mapp Assunto da revista: CEREBRO Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Alemanha