Sequence-dependent predictive coding during the learning and rewiring of skills

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Ádám Takács - , Department of Child and Adolescent Psychiatry and Psychotherapy (Author)
  • Teodóra Vékony - , University of Atlántico Medio, Lyon Neuroscience Research Center (CRNL) (Author)
  • Felipe Pedraza - , Lyon Neuroscience Research Center (CRNL), Université Lumière Lyon 2 (Author)
  • Frederic Haesebaert - , Lyon Neuroscience Research Center (CRNL) (Author)
  • Barbara Tillmann - , Université de Bourgogne (Author)
  • Christian Beste - , Department of Child and Adolescent Psychiatry and Psychotherapy (Author)
  • Dezso Németh - , University of Atlántico Medio, Lyon Neuroscience Research Center (CRNL), Hungarian Academy of Sciences (Author)

Abstract

In the constantly changing environment that characterizes our daily lives, the ability to predict and adapt to new circumstances is crucial. This study examines the influence of sequence and knowledge adaptiveness on predictive coding in skill learning and rewiring. Participants were exposed to two different visuomotor sequences with overlapping probabilities. By applying temporal decomposition and multivariate pattern analysis, we dissected the neural underpinnings across different levels of signal coding. The study provides neurophysiological evidence for the influence of knowledge adaptiveness on shaping predictive coding, revealing that these are intricately linked and predominantly manifest at the abstract and motor coding levels. These findings challenge the traditional view of a competitive relationship between learning context and knowledge, suggesting instead a hierarchical integration where their properties are processed simultaneously. This integration facilitates the adaptive reuse of existing knowledge in the face of new learning. By shedding light on the mechanisms of predictive coding in visuomotor sequences, this research contributes to a deeper understanding of how the brain navigates and adapts to environmental changes, offering insights into the foundational processes that underlie learning and adaptation in dynamic contexts.

Details

Original languageEnglish
Article numberbhaf025
JournalCerebral cortex
Volume35
Issue number2
Publication statusPublished - Feb 2025
Peer-reviewedYes

External IDs

PubMed 39989199
ORCID /0000-0002-2989-9561/work/187562774

Keywords

Keywords

  • electrophysiology, multivariate pattern analysis, skill learning, statistical learning