Longitudinal markers of cognitive procedural learning in fronto-striatal circuits and putative effects of a BDNF plasticity-related variant

Procedural learning and automatization have widely been studied in behavioral psychology and typically involves a rapid improvement, followed by a plateau in performance throughout repeated training. More recently, brain imaging studies have implicated frontal-striatal brain circuits in skill learning. However, it is largely unknown whether frontal-striatal activation during skill learning and behavioral changes follow a similar learning curve pattern. To address this gap in knowledge, we performed a longitudinal brain imaging study using a procedural working memory (pWM) task with repeated measurements across two weeks to map the temporal dynamics of skill learning. We additionally explored the effect of the BDNF Val<sup>66</sup>Met polymorphism, a common genetic polymorphism impacting neural plasticity, to further inform the relevance of the identified neural markers. We used linear and exponential modeling to characterize procedural learning by means of learning curves on the behavioral and brain functional level. We show that repeated training led to an exponential decay in a distributed set of brain regions including fronto-striatal circuits, which paralleled the exponential improvement in task performance. In addition, we show that both behavioral and neurofunctional readouts were sensitive to the BDNF Val<sup>66</sup>Met polymorphism, suggesting less efficient learning in <sup>66</sup>Met-allele carriers along with protracted signal decay in frontal and striatal brain regions. Our results extend existing literature by showing the temporal relationship between procedural learning and frontal-striatal brain function and suggest a role of BDNF in mediating neural plasticity for establishing automatized behavior.

Authors

Institutions

Publication Details

Journal
npj Science of Learning
Published
2024-11-28
DOI
https://doi.org/10.1038/s41539-024-00282-2
Citations
3
Primary Topic
Neural and Behavioral Psychology Studies
Type
article
Field-Weighted Citation Impact
1.03

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Longitudinal markers of cognitive procedural learning in fronto-striatal circuits and putative effects of a BDNF plasticity-related variant

Andreas Meyer‐Lindenberg, Stefan Herms, Zhenxiang Zang, Stephanie H. Witt et al.
3 citations
npj Science of Learning
Neural and Behavioral Psychology Studies
1.03
article

Longitudinal markers of cognitive procedural learning in fronto-striatal circuits and putative effects of a BDNF plasticity-related variant

Andreas Meyer‐Lindenberg, Stefan Herms, Zhenxiang Zang, Stephanie H. Witt, Mark Melzer, Carolin Moessnang, Torsten Wüstenberg, Lena S. Geiger, Franziska Degenhardt, Marcella Rietschel, Markus M. Nöthen
article en
3 citations

Abstract

Procedural learning and automatization have widely been studied in behavioral psychology and typically involves a rapid improvement, followed by a plateau in performance throughout repeated training. More recently, brain imaging studies have implicated frontal-striatal brain circuits in skill learning. However, it is largely unknown whether frontal-striatal activation during skill learning and behavioral changes follow a similar learning curve pattern. To address this gap in knowledge, we performed a longitudinal brain imaging study using a procedural working memory (pWM) task with repeated measurements across two weeks to map the temporal dynamics of skill learning. We additionally explored the effect of the BDNF Val<sup>66</sup>Met polymorphism, a common genetic polymorphism impacting neural plasticity, to further inform the relevance of the identified neural markers. We used linear and exponential modeling to characterize procedural learning by means of learning curves on the behavioral and brain functional level. We show that repeated training led to an exponential decay in a distributed set of brain regions including fronto-striatal circuits, which paralleled the exponential improvement in task performance. In addition, we show that both behavioral and neurofunctional readouts were sensitive to the BDNF Val<sup>66</sup>Met polymorphism, suggesting less efficient learning in <sup>66</sup>Met-allele carriers along with protracted signal decay in frontal and striatal brain regions. Our results extend existing literature by showing the temporal relationship between procedural learning and frontal-striatal brain function and suggest a role of BDNF in mediating neural plasticity for establishing automatized behavior.

npj Science of LearningVol. 9(1)
University of Bonn (DE), Heidelberg University (DE), University Hospital Bonn (DE), University Hospital Heidelberg (DE), SRH University of Applied Sciences Heidelberg (DE), Central Institute of Mental Health (DE), STZ eyetrial (DE), University of Duisburg-Essen (DE)
Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung
Openalex Percentile: Top 23%
Neural and Behavioral Psychology Studies
1.03
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.