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Post-error slowing is associated with intelligence

Author

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  • Varriale, Vincenzo
  • De Pascalis, Vilfredo
  • van der Molen, Maurits W.

Abstract

There is considerable evidence showing that people slow down after making an error. The post-error slowing is typically interpreted as the result of adaptation processes raising response criteria in order to avoid future errors. Here we analyze performance results of a previous study examining the relation between intelligence and electrocortical concomitants of mental rotation. Participants performed a hybrid Choice/Go-NoGo task presenting stimuli upright or rotated (60, 120, or 180 degrees) in normal or mirror image. The results showed that low-ability participants responded slower overall and committed more errors—in particular on NoGo trials with 180 degrees rotated stimuli. We selected the error trials and 7 correct Go trials preceding the error trial and 3 correct Go trials following the error trial. The results showed considerable post-error slowing and revealed that this slowing was related to intelligence—low-ability participants showed greater slowing than high-ability participants. This finding was interpreted within the context of diffusion-modeling studies of post-error slowing and may suggest that the rate of evidence accumulation and, possibly, the setting of response thresholds on trials following an error is more vulnerable in low- relative to high-ability individuals.

Suggested Citation

  • Varriale, Vincenzo & De Pascalis, Vilfredo & van der Molen, Maurits W., 2021. "Post-error slowing is associated with intelligence," Intelligence, Elsevier, vol. 89(C).
    • Handle: RePEc:eee:intell:v:89:y:2021:i:c:s0160289621000830
    DOI: 10.1016/j.intell.2021.101599
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    References listed on IDEAS

    as
    1. Varriale, Vincenzo & van der Molen, Maurits W. & De Pascalis, Vilfredo, 2018. "Mental rotation and fluid intelligence: A brain potential analysis," Intelligence, Elsevier, vol. 69(C), pages 146-157.
    2. Alexandra Woolgar & John Duncan & Facundo Manes & Evelina Fedorenko, 2018. "Fluid intelligence is supported by the multiple-demand system not the language system," Nature Human Behaviour, Nature, vol. 2(3), pages 200-204, March.
    3. Liang, Feng & Paulo, Rui & Molina, German & Clyde, Merlise A. & Berger, Jim O., 2008. "Mixtures of g Priors for Bayesian Variable Selection," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 410-423, March.
    4. Renata Figueiredo Anomal & Daniel Soares Brandão & Silvia Beltrame Porto & Sóstenes Silva de Oliveira & Rafaela Faustino Lacerda de Souza & José de Santana Fiel & Bruno Duarte Gomes & Izabel Augusta H, 2020. "The role of frontal and parietal cortex in the performance of gifted and average adolescents in a mental rotation task," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-21, May.
    5. repec:cup:judgdm:v:11:y:2016:i:2:p:174-184 is not listed on IDEAS
    6. Glenn N Saxe & Daniel Calderone & Leah J Morales, 2018. "Brain entropy and human intelligence: A resting-state fMRI study," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-21, February.
    7. Sarah E Forster & Raymond Y Cho, 2014. "Context Specificity of Post-Error and Post-Conflict Cognitive Control Adjustments," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-13, March.
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