The DOI matches its Crossref record; 62 of the 64 references it cites were found in a registry or an index.
Predicting events of varying probability: uncertainty investigated by fMRI
Open accessAbstract
Many everyday life predictions rely on the experience and memory of event frequencies, i.e., natural samplings. We used functional magnetic resonance imaging (fMRI) to investigate the neural substrates of prediction under varying uncertainty based on a natural sampling approach. The study focused particularly on a comparison with other types of externally attributed uncertainty, such as guessing, and on the frontomedian cortex, which is known to be engaged in many types of decisions under uncertainty. On the basis of preceding stimulus cues, participants predicted events that occurred with probabilities ranging from p = 0.6 to p = 1.0. In contrast to certain predictions in a control task, predictions under uncertainty elicited activations within a posterior frontomedian area (mesial BA 8) and within a set of subcortical areas which are known to subserve dopaminergic modulations. The parametric analysis revealed that activation within the mesial BA 8 significantly increased with increasing uncertainty. A comparison with other types of uncertainty indicates that frontomedian correlates of frequency-based prediction appear to be comparable with those induced in long-term stimulus-response adaptation processes such as hypothesis testing, in contrast to those engaged in short-term error processing such as guessing.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The greater recruitment of ACC in children, a region involved in conflict monitoring (van Veen and Carter, 2002) and anticipation of uncertain outcome (Volz et al., 2003) suggests that children are less efficient than adolescents or adults at processing uncertainty.”
From A systematic review of fMRI reward paradigms used in studies of adolescents vs. adults: The impact of task design and implications for understanding neurodevelopment (2013) · cites this paper as Volz et al., 2003
Citations
Cites
Predictive reward signal of dopamine neurons
Schultz, W. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.80.1.1 · Cited by 4,564
Automatic and effortful processes in memory.
Hasher, L., & Zacks, R. T. (1979) · Journal of Experimental Psychology: General · doi:10.1037/0096-3445.108.3.356 · Cited by 2,812
Li, T.-H. (2013) · Chapman & Hall/CRC eBooks · doi:10.1201/b15154-8 · Cited by 2,751
Analysis of fMRI Time-Series Revisited—Again
Worsley, K. J., & Friston, K. J. (1995) · NeuroImage · doi:10.1006/nimg.1995.1023 · Cited by 2,198
How to improve Bayesian reasoning without instruction: Frequency formats.
Gigerenzer, G., & Hoffrage, U. (1995) · Psychological Review · doi:10.1037/0033-295x.102.4.684 · Cited by 2,190
Emotion and motivation: the role of the amygdala, ventral striatum, and prefrontal cortex
Cardinal, R. N., Parkinson, J. A., Hall, J., & Everitt, B. J. (2002) · Neuroscience & Biobehavioral Reviews · doi:10.1016/s0149-7634(02)00007-6 · Cited by 2,129
Event-Related fMRI: Characterizing Differential Responses
Friston, K. J., Fletcher, P. C., Josephs, O., Holmes, A., Rugg, M. D., & Turner, R. (1998) · NeuroImage · doi:10.1006/nimg.1997.0306 · Cited by 2,017
Abstract reward and punishment representations in the human orbitofrontal cortex
O'Doherty, J., Kringelbach, M. L., Rolls, E. T., Hornak, J., & Andrews, C. (2001) · Nature Neuroscience · doi:10.1038/82959 · Cited by 2,003
Motor Areas of the Medial Wall: A Review of Their Location and Functional Activation
Picard, N., & Strick, P. L. (1996) · Cerebral Cortex · doi:10.1093/cercor/6.3.342 · Cited by 1,712
Neuronal Coding of Prediction Errors
Schultz, W., & Dickinson, A. (2000) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.23.1.473 · Cited by 1,427
Cited by
Sorted by citations
Items 201–214 of 214
Neural and Hormonal Systems Underlying Human Reward-Seeking Behavior
Dunne, S. (2016) · CaltechTHESIS (California Institute of Technology) · doi:10.7907/z9sn06zx
Psychopathy and Human judgement: a personality view of criminal decision-making
Luís, J. C. D. S. P. (2019) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · doi:10.34626/ypz3-vm67
Imaging of obsessive–compulsive disorder
Shahab, R., & Stern, E. R. (2020) · doi:10.1093/med/9780198713005.003.0097
Geng, H. (2020) · University of Groningen research database (University of Groningen / Centre for Information Technology) · doi:10.33612/diss.131330743
Current Awareness in NMR in Biomedicine
(2003) · NMR in Biomedicine · doi:10.1002/nbm.804
Burgos, J. E. (2017) · Springer eBooks · doi:10.1007/978-3-319-47829-6_1066-1
Burgos, J. E. (2022) · Springer eBooks · doi:10.1007/978-3-319-55065-7_1066
Dopamine et contrôle de l’action : implication et maturation de la voie mésocorticale chez le rat
Naneix, F. (2011) · theses.fr (ABES) · doi:10.70675/001d4221ze950z4b8dz8178z8e2211b1bc4c
RETRACTED: Neural correlates of risky monetary decision-making impacting others
Fede, S. J., Jefferson, Y., & Romines, A. J. (2026) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2026.1813515
“…compared high probability and low probability outcomes (rather than certain versus uncertain here); other work suggests we can expect there to be neural differences in how certain versus uncertain outcomes are processed (Volz et al., 2003) and as a function of probability (Seaman et al., 2018).”
RetractedCai, X., Wu, M., Tang, H., Yang, R., & Fan, J. (2026) · Behavioral Sciences · doi:10.3390/bs16091518
“…processing (Feng et al., 2022; Wu et al., 2021), parietal regions are not specific to ambiguity and have been implicated in probability-based decision variables, action selection, and the integration of decision-relevant information (Platt & Glimcher, 1999; Huettel, 2006; Volz et al., 2003).”
Serrao, F., Mauri, M., Gallace, A., Gallucci, M., & Gabbiadini, A. (2026) · Journal of Psychophysiology · doi:10.1027/0269-8803/a000363
Franssen, M., Gao, R., van der Spek, E. D., & Martens, M. H. (2026) · Behaviour and Information Technology · doi:10.1080/0144929x.2026.2746452
Franssen, M., van der Spek, E. D., & Martens, M. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1917625
Metadata
- Authors
- Volz, K. G., Schubotz, R. I., & von Cramon, D. Y.
- Affiliations
- Max Planck Society (DE)
- Corresponding author
- Volz, Kirsten G
- ORCID
- Schubotz, Ricarda I
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2003-06
- Volume
- 19
- Issue
- 2
- Pages
- 271-280
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2101401693
- Cited by
- 214
- References
- 64
- Citations by year
- 2026: 5 · 2025: 5 · 2024: 3 · 2023: 4 · 2022: 5 · 2021: 4 · 2020: 6 · 2019: 11 · 2018: 6 · 2017: 11 · 2016: 11 · 2015: 6 · 2014: 10 · 2013: 13 · 2012: 9
- FWCI
- 6.21
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Max Planck Institute for Plasma Physics (submittedVersion)
- Max Planck Digital Library (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- Funders
- Deutsche Forschungsgemeinschaft
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- prediction under uncertainty, natural sampling, dopaminergic modulation, guessing, hypothesis testing, error processing
- MeSH terms
- Adult, Arousal, Brain, Brain Mapping, Female, Frontal Lobe, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Neural Pathways, Oxygen Consumption, Pattern Recognition, Visual, Probability Learning, Problem Solving, Psychomotor Performance, Mental Recall, Reference Values, Imaging, Three-Dimensional
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review