ArticleAttention, perception & psychophysics2026
Predicting errors before they occur using trial-by-trial dynamics of pre-error and post-error behavior.
Article in Attention, perception & psychophysics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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.
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Authors and funding
4 authors.
Funding
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Abstract
Errors rarely occur in isolation, but rather within behavioral sequences and are known to shape subsequent behavior. However, understanding the full time course of the impact of errors has been challenging given data limitations. Here, to gain key insights, two groups of precisely matched participants (n > 35,000) were compared; those who made versus did not make an error in a short object discrimination task. Linear mixed-effects models revealed error-induced effects both preceding and following errors. First, the error group showed pre-error speeding up to eight trials before the error occurred. Second, post-error slowing occurred and rapidly diminished over trials. Finally, leave-one-out cross-validation models using individual trial behavior predicted an upcoming error eight trials before the error occurred. This project highlights the systematic nature of behavioral changes around errors and demonstrates the potential for early error prediction and intervention using only simple metrics and models.
Indexed as
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42215806What Socratic holds
Registered trials
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 Socratic graph.