People differ in the belief that their intuitions produce good decision outcomes. In the present research, we sought to test the validity of these beliefs by comparing individuals' self-reports with measures of actual intuition performance in a standard implicit learning task, exposing participants to seemingly random letter strings (Studies 1a-b) and social media profile pictures (Study 2) that conformed to an underlying rule or grammar. A meta-analysis synthesizing the present data ( = 400) and secondary data by Pretz, Totz, and Kaufman found that people's enduring beliefs in their intuitions were not reflective of actual performance in the implicit learning task. Meanwhile, task-specific confidence in intuition bore no sizable relation with implicit learning performance, but the observed data favoured neither the null hypothesis nor the alternative hypothesis. Together, the present findings suggest that people's ability to judge the veracity of their intuitions may be limited.
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http://dx.doi.org/10.1177/1948550617706732 | DOI Listing |
J Neurophysiol
January 2025
KU Leuven, Department of Movement Sciences, B-3000 Leuven, Belgium.
In motor adaptation, learning is thought to rely on a combination of several processes. Two of these are implicit learning (incidental updating of the movement due to sensory prediction error) and explicit learning (intentional adjustment to reduce target error). The explicit component is thought to be fast adapting, while the implicit one is slow.
View Article and Find Full Text PDFPLoS One
January 2025
Neurorehabilitation and Biomechanics Research Section, Rehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD, United States of America.
Children with cerebral palsy (CP) often participate in training to improve mobility, hand function and other motor abilities. However, responses to these interventions vary considerably across individuals even those with similar brain injuries, ages and functional levels. Dopamine is a neurotrasmitter known to affect motor skill acquistion in animals and humans and may be influenced by individual variations in genes related to brain transmission of dopamine.
View Article and Find Full Text PDFNat Rev Neurosci
January 2025
Intramural Research Program, National Institute on Drug Abuse, Baltimore, MD, USA.
Transient changes in the firing of midbrain dopamine neurons have been closely tied to the unidimensional value-based prediction error contained in temporal difference reinforcement learning models. However, whereas an abundance of work has now shown how well dopamine responses conform to the predictions of this hypothesis, far fewer studies have challenged its implicit assumption that dopamine is not involved in learning value-neutral features of reward. Here, we review studies in rats and humans that put this assumption to the test, and which suggest that dopamine transients provide a much richer signal that incorporates information that goes beyond integrated value.
View Article and Find Full Text PDFBioengineering (Basel)
December 2024
Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford OX3 7DQ, UK.
Cardiovascular diseases (CVDs) are the most common health threats worldwide. 2D X-ray invasive coronary angiography (ICA) remains the most widely adopted imaging modality for CVD assessment during real-time cardiac interventions. However, it is often difficult for the cardiologists to interpret the 3D geometry of coronary vessels based on 2D planes.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
January 2025
QUEST Center for Responsible Research, Berlin Institute of Health at Charité Universitätsmedizin Berlin, Berlin, Germany.
Background: Machine learning (ML) is increasingly used to predict clinical deterioration in intensive care unit (ICU) patients through scoring systems. Although promising, such algorithms often overfit their training cohort and perform worse at new hospitals. Thus, external validation is a critical - but frequently overlooked - step to establish the reliability of predicted risk scores to translate them into clinical practice.
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