Evidence map›Paper›PMID 42905440›Full record

ArticleeLife2026

Strong mnemonic prediction errors increase cognitive control, attention, and arousal.

Alice M Xue, Jenna Jokhani, Anthony M Norcia, Anthony D Wagner

Abstract read
In one paragraph

Article in eLife, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Alice M XueDepartment of Psychology, Stanford University, Stanford, United States.ORCID https://orcid.org/0009-0006-3176-8786
Jenna JokhaniDepartment of Psychology, Stanford University, Stanford, United States.
Anthony M NorciaDepartment of Psychology, Stanford University, Stanford, United States.
Anthony D WagnerDepartment of Psychology, Stanford University, Stanford, United States.ORCID https://orcid.org/0000-0003-0624-4543

Funding

Effects of attention and goal-state lapses on memory in healthy and pathological agingR01AG065255 · NIA · STANFORD UNIVERSITY · PI WAGNER, ANTHONY D · 2020 to 2024
$3.7M
National Science Foundation Graduate Research Fellowship Program DGE-2146755NIA NIH HHS R01AG065255Stanford University Stanford Interdisciplinary Graduate Fellowship
6 · The paper itself

Abstract

Ongoing experience is continuously processed in the context of past events. Divergence between current experience and memory-based predictions (i.e., a mnemonic prediction error; MPE) is theorized to be a signal that encoding, as opposed to retrieval, should be prioritized. We asked how MPEs place demands on control and attention-related processes, and whether these demands differ as a function of prediction strength. We investigated these questions across two experiments, wherein we recorded scalp electroencephalography and/or pupillometry as 101 young human adults performed an associative memory task. Strong MPEs, more so than weak MPEs, increased physiological indices of cognitive control (frontal theta), attention (posterior alpha and pupil size), and arousal (pupil size). Greater cognitive control (frontal theta) during strong MPEs promoted better learning of prediction-violating (i.e., unexpected) stimuli. Collectively, these findings reveal multiple pathways through which the mind and brain respond adaptively to violations of strong mnemonic predictions.

Indexed as

ArousalAttentionCognitionMemoryAdultBrainElectroencephalographyFemaleHumansMalePupilYoung Adultarousalattentioncognitive controlepisodic memoryhumanlearningneuroscienceprediction error

Identifiers

PMID42905440
PMCPMC13686618

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.