Evidence map›Paper›PMID 33147209›Full record

ArticlePLoS computational biology2020

PPM-Decay: A computational model of auditory prediction with memory decay.

Peter M C Harrison, Roberta Bianco, Maria Chait, Marcus T Pearce

Erratum issuedAbstract read
In one paragraph

Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Discovery, Interruption, and Updating of Auditory Regularities in Memory: Evidence from Low-Frequency Brain Dynamics in Human MEG.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  2. Review
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  4. Article
  5. Humans can find rhythm in randomly timed sounds.Royal Society open science · 2025
    Article
  6. Article
  7. Concurrent Encoding of Sequence Predictability and Event-Evoked Prediction Error in Unfolding Auditory Patterns.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Article
  8. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Peter M C HarrisonComputational Auditory Perception Research Group, Max Planck Institute for Empirical Aesthetics, Frankfurt, Germany.ORCID 0000-0002-9851-9462
Roberta BiancoUCL Ear Institute, University College London, London, UK.ORCID 0000-0001-9613-8933
Maria ChaitUCL Ear Institute, University College London, London, UK.ORCID 0000-0002-7808-3593
Marcus T PearceCognitive Science Research Group, Queen Mary University of London, London, UK.ORCID 0000-0002-1282-431X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Statistical learning and probabilistic prediction are fundamental processes in auditory cognition. A prominent computational model of these processes is Prediction by Partial Matching (PPM), a variable-order Markov model that learns by internalizing n-grams from training sequences. However, PPM has limitations as a cognitive model: in particular, it has a perfect memory that weights all historic observations equally, which is inconsistent with memory capacity constraints and recency effects observed in human cognition. We address these limitations with PPM-Decay, a new variant of PPM that introduces a customizable memory decay kernel. In three studies-one with artificially generated sequences, one with chord sequences from Western music, and one with new behavioral data from an auditory pattern detection experiment-we show how this decay kernel improves the model's predictive performance for sequences whose underlying statistics change over time, and enables the model to capture effects of memory constraints on auditory pattern detection. The resulting model is available in our new open-source R package, ppm (https://github.com/pmcharrison/ppm).

Indexed as

Auditory PerceptionComputer SimulationMemoryAlgorithmsHumansMusic

Identifiers

PMID33147209
PMCPMC7668605

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.