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

A predictive processing model of episodic memory and time perception

View ORCID ProfileZafeirios Fountas, Anastasia Sylaidi, View ORCID ProfileKyriacos Nikiforou, View ORCID ProfileAnil K. Seth, View ORCID ProfileMurray Shanahan, View ORCID ProfileWarrick Roseboom
doi: https://doi.org/10.1101/2020.02.17.953133
Zafeirios Fountas
3Emotech Labs, London, UK
4Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Zafeirios Fountas
  • For correspondence: fountas@outlook.com
Anastasia Sylaidi
1Department of Computing, Imperial College London, London, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kyriacos Nikiforou
1Department of Computing, Imperial College London, London, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Kyriacos Nikiforou
Anil K. Seth
2Department of Informatics and Sackler Centre for Consciousness Science, University of Sussex, Sussex, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Anil K. Seth
Murray Shanahan
1Department of Computing, Imperial College London, London, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Murray Shanahan
Warrick Roseboom
2Department of Informatics and Sackler Centre for Consciousness Science, University of Sussex, Sussex, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Warrick Roseboom
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

ABSTRACT

Human perception and experience of time is strongly affected by environmental context. When paying close attention to time, time experience seems to expand; when distracted from time, experience of time seems to contract. Contrasts in experiences like these are common enough to be exemplified in sayings like “time flies when you’re having fun”. Similarly, experience of time depends on the content of perceptual experience – more rapidly changing or complex perceptual scenes seem longer in duration than less dynamic ones. The complexity of interactions among stimulation, attention, and memory that characterise time experience is likely the reason that a single overarching theory of time perception has been difficult to achieve. In the present study we propose a framework that reconciles these interactions within a single model, built using the principles of the predictive processing approach to perception. We designed a neural hierarchical Bayesian system, functionally similar to human perceptual processing, making use of hierarchical predictive coding, short-term plasticity, spatio-temporal attention, and episodic memory formation and recall. A large-scale experiment with ∼ 13,000 human participants investigated the effects of memory, cognitive load, and stimulus content on duration reports of natural scenes up to ∼ 1 minute long. Model-based estimates matched human reports, replicating key qualitative biases including differences by cognitive load, scene type, and judgement (prospective or retrospective). Our approach provides an end-to-end model of duration perception from natural stimulus processing to estimation and from current experience to recalling the past, providing a new understanding of this central aspect of human experience.

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 4.0 International license.
Back to top
PreviousNext
Posted February 17, 2020.
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.
A predictive processing model of episodic memory and time perception
(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
A predictive processing model of episodic memory and time perception
Zafeirios Fountas, Anastasia Sylaidi, Kyriacos Nikiforou, Anil K. Seth, Murray Shanahan, Warrick Roseboom
bioRxiv 2020.02.17.953133; doi: https://doi.org/10.1101/2020.02.17.953133
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
A predictive processing model of episodic memory and time perception
Zafeirios Fountas, Anastasia Sylaidi, Kyriacos Nikiforou, Anil K. Seth, Murray Shanahan, Warrick Roseboom
bioRxiv 2020.02.17.953133; doi: https://doi.org/10.1101/2020.02.17.953133

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 (4382)
  • Biochemistry (9591)
  • Bioengineering (7090)
  • Bioinformatics (24858)
  • Biophysics (12610)
  • Cancer Biology (9956)
  • Cell Biology (14350)
  • Clinical Trials (138)
  • Developmental Biology (7948)
  • Ecology (12105)
  • Epidemiology (2067)
  • Evolutionary Biology (15988)
  • Genetics (10925)
  • Genomics (14738)
  • Immunology (9869)
  • Microbiology (23660)
  • Molecular Biology (9484)
  • Neuroscience (50860)
  • Paleontology (369)
  • Pathology (1539)
  • Pharmacology and Toxicology (2682)
  • Physiology (4013)
  • Plant Biology (8657)
  • Scientific Communication and Education (1508)
  • Synthetic Biology (2394)
  • Systems Biology (6433)
  • Zoology (1346)