Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Statistical learning of successor representations is related to on-task replay

View ORCID ProfileLennart Wittkuhn, Lena M. Krippner, View ORCID ProfileNicolas W. Schuck
doi: https://doi.org/10.1101/2022.02.02.478787
Lennart Wittkuhn
1Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, Berlin, Germany
2Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany Lentzeallee 94, D–14195 Berlin, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Lennart Wittkuhn
  • For correspondence: wittkuhn@mpib-berlin.mpg.de schuck@mpib-berlin.mpg.de
Lena M. Krippner
1Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, Berlin, Germany
3Harding Center for Risk Literacy, University of Potsdam, Faculty of Health Sciences, Potsdam, Germany Virchowstraße 2–4, D–14482 Potsdam, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nicolas W. Schuck
1Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, Berlin, Germany
2Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany Lentzeallee 94, D–14195 Berlin, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Nicolas W. Schuck
  • For correspondence: wittkuhn@mpib-berlin.mpg.de schuck@mpib-berlin.mpg.de
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

Humans automatically infer higher-order relationships between events in the environment from their statistical co-occurrence, often without conscious awareness. Neural replay of task representations, which has been described as sampling from a learned transition structure of the environment, is a candidate mechanism by which the brain could use or even learn such relational information in the service of adaptive behavior. Human participants viewed sequences of images that followed probabilistic transitions determined by ring-like graph structures. Behavioral modeling revealed that participants acquired multi-step transition knowledge through gradual updating of an internal successor representation (SR) model, although half of participants did not indicate any knowledge about the sequential task structure. To investigate neural replay, we analyzed dynamics of multivariate functional magnetic resonance imaging (fMRI) patterns during short pauses from the ongoing statistical learning task. Evidence for sequential replay consistent with the probabilistic task structure was found in occipito-temporal and sensorimotor cortices during short on-task intervals. These findings indicate that implicit learning of higher-order relationships establishes an internal SR-based map of the task, and is accompanied by cortical on-task replay.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted February 02, 2022.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Statistical learning of successor representations is related to on-task replay
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Statistical learning of successor representations is related to on-task replay
Lennart Wittkuhn, Lena M. Krippner, Nicolas W. Schuck
bioRxiv 2022.02.02.478787; doi: https://doi.org/10.1101/2022.02.02.478787
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Statistical learning of successor representations is related to on-task replay
Lennart Wittkuhn, Lena M. Krippner, Nicolas W. Schuck
bioRxiv 2022.02.02.478787; doi: https://doi.org/10.1101/2022.02.02.478787

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Neuroscience
Subject Areas
All Articles
  • Animal Behavior and Cognition (4655)
  • Biochemistry (10307)
  • Bioengineering (7618)
  • Bioinformatics (26203)
  • Biophysics (13453)
  • Cancer Biology (10625)
  • Cell Biology (15348)
  • Clinical Trials (138)
  • Developmental Biology (8456)
  • Ecology (12761)
  • Epidemiology (2067)
  • Evolutionary Biology (16777)
  • Genetics (11361)
  • Genomics (15407)
  • Immunology (10556)
  • Microbiology (25060)
  • Molecular Biology (10162)
  • Neuroscience (54128)
  • Paleontology (398)
  • Pathology (1655)
  • Pharmacology and Toxicology (2877)
  • Physiology (4315)
  • Plant Biology (9204)
  • Scientific Communication and Education (1582)
  • Synthetic Biology (2543)
  • Systems Biology (6753)
  • Zoology (1453)