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

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Ádám Takács - , Klinik und Poliklinik für Kinder- und Jugendpsychiatrie (Autor:in)
  • Teodóra Vékony - , Universidad del Atlántico Medio, Centre de Recherche en Neurosciences de Lyon (Autor:in)
  • Felipe Pedraza - , Centre de Recherche en Neurosciences de Lyon, Universität Lyon II (Autor:in)
  • Frederic Haesebaert - , Centre de Recherche en Neurosciences de Lyon (Autor:in)
  • Barbara Tillmann - , Université de Bourgogne (Autor:in)
  • Christian Beste - , Klinik und Poliklinik für Kinder- und Jugendpsychiatrie (Autor:in)
  • Dezso Németh - , Universidad del Atlántico Medio, Centre de Recherche en Neurosciences de Lyon, Magyar Tudományos Akadémia (Autor:in)

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

OriginalspracheEnglisch
Aufsatznummerbhaf025
FachzeitschriftCerebral cortex
Jahrgang35
Ausgabenummer2
PublikationsstatusVeröffentlicht - Feb. 2025
Peer-Review-StatusJa

Externe IDs

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

Schlagworte

Schlagwörter

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