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Neural correlates of developmental differences in risk estimation and feedback processing
Abstract
The primary aim of this study was to compare the neural substrates of decision-making in middle-aged children and adults. To this end, we collected fMRI data while 9-12-year-olds and 18-26-year-olds performed a simple gambling task. The task was designed to tap two important aspects of decision-making: risk estimation and feedback processing. We examined how orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), and dorsolateral prefrontal cortex (DLPFC) contributed to risk estimation, and how ventrolateral and medial prefrontal cortices (VLPFC and medial PFC) contributed to negative feedback processing in children and adults. Region of interest analyses revealed differences in brain activation between children and adults for ACC and lateral OFC. ACC was recruited more for high-risk than for low-risk trials, and this difference was larger for children than for adults. In contrast, children and adults did not differ in activation for OFC or DLPFC. These data suggest that children's decision-making under uncertainty is associated with a high degree of response conflict. Both age groups exhibited bilateral VLPFC (BA 47) and medial PFC/ACC (BA 6/ BA 32 (dorsal) and 24 (ventral)) activation associated with negative feedback processing. Relative to adults, children engaged lateral OFC more strongly for negative relative to positive feedback. These results indicate that children may find negative feedback more aversive than adults do. In summary, children aged 9-12 years and adults recruit similar brain regions during risk-estimation and feedback processing, but some key differences between the groups provide insight into the factors contributing to developmental changes in decision-making.
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In the citing paper
“For example, the first version of the Cake Gambling task (Van Leijenhorst et al., 2006) has been framed as making a decision for the reward underlying the largest piece of cake, leading this task to be referred to as a “reward decision-making task”; however, we place this task in the category of “instrumental-reward tasks”, because there is an uncontroversial correct and incorrect response, the”
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 Van Leijenhorst et al., 2006
In the citing paper
“during the selection stage, the medial PFC/anterior cingulate cortex (ACC; MNI 0, 6, 20) was activated more in children than in adults for low vs. high probability trials.”
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 Van Leijenhorst et al., 2006
In the citing paper
“Collectively, the findings of Van Leijenhorst et al. (2006), Galvan et al. (2006), and Somerville et al. (2010) support a stronger recruitment of striatal function relative to OFC function, in adolescents relative to adults.”
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 Van Leijenhorst et al. (2006)
In the citing paper
“during the feedback stage, the OFC (MNI 40, 46, −12) was more sensitive to negative than positive feedback in children than in adults.”
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 Van Leijenhorst et al., 2006
In the citing paper
“the dorsolateral PFC (DLPFC) and OFC were both more activated to low probability than high probability trials, but these activations were not influenced by age”
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 Van Leijenhorst et al., 2006
In the citing paper
“During the actual cognitive/motor stage, prefrontal cortical regions (IFG and DLPFC) were more active in youths than in adults on non-rewarded trials (Somerville and Casey, 2010; Van Leijenhorst et al., 2006).”
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 Van Leijenhorst et al., 2006
In the citing paper
“during positive feedback stage, stronger striatal activation (Cohen et al., 2010), and during negative feedback, weaker OFC activation (Van Leijenhorst et al., 2006), emerged in adolescents compared to adults.”
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 Van Leijenhorst et al., 2006
Citations
Cites
Co-Planar Stereotaxic Atlas of the Human Brain
Talairach, J., & Tournoux, P. (1988) · Medical Entomology and Zoology · Cited by 11,798
Insensitivity to future consequences following damage to human prefrontal cortex
Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994) · Cognition · doi:10.1016/0010-0277(94)90018-3 · Cited by 6,128
Deciding advantageously before knowing the advantageous strategy
Bechara, A., Damasio, H., Tranel, D., & Damasio, A. R. (1997) · Science · doi:10.1126/science.275.5304.1293 · Cited by 3,547
Delay of gratification in children.
Mischel, W., Shoda, Y., & Rodriguez, M. L. (1989) · Science · doi:10.1126/science.2658056 · Cited by 3,397
Anterior Cingulate Cortex, Error Detection, and the Online Monitoring of Performance
Carter, C. S., Braver, T. S., Barch, D. M., Botvinick, M. M., Noll, D., & Cohen, J. D. (1998) · Science · doi:10.1126/science.280.5364.747 · Cited by 3,273
Separate neural systems value immediate and delayed monetary rewards
McClure, S. M., Laibson, D. I., Loewenstein, G., & Cohen, J. D. (2004) · Science · doi:10.1126/science.1100907 · Cited by 3,089
Cognitive and affective development in adolescence
Steinberg, L. (2005) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2004.12.005 · Cited by 2,978
Region of interest analysis using an SPM toolbox
Brett, M. (2002) · NeuroImage · Cited by 2,273
Anticipation of Increasing Monetary Reward Selectively Recruits Nucleus Accumbens
Knutson, B., Adams, C. M., Fong, G. W., & Hommer, D. (2001) · The Journal of Neuroscience · doi:10.1523/jneurosci.21-16-j0002.2001 · Cited by 2,244
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
Research works printed but not linked: 1
- Cocosco, 1997, Brain Web: Online interface to a 3D MRI simulated brain database, Neuroimage, 5, S425
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Delgado, A. O., & Suárez, L. A. (2010) · Studies in Psychology Estudios de Psicología · doi:10.1174/021093910790744563 · Cited by 20
Early tobacco smoking in adolescents with externalizing disorders: Inferences for reward function
Aklin, W. M., Moolchan, E. T., Luckenbaugh, D. A., & Ernst, M. (2009) · Nicotine & Tobacco Research · doi:10.1093/ntr/ntp059 · Cited by 14
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Luking, K. R., Pagliaccio, D., Luby, J. L., & Barch, D. M. (2015) · Emotion · doi:10.1037/emo0000122 · Cited by 14
Wang, J., Cao, B., Cai, X., Gao, H., & Li, F. (2015) · PLoS ONE · doi:10.1371/journal.pone.0140731 · Cited by 13
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Pei, R., Kranzler, E. C., Suleiman, A. B., & Falk, E. B. (2018) · Behavioural Public Policy · doi:10.1017/bpp.2018.30 · Cited by 12
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Dion, J.-S., & Restrepo, G. (2016) · Zeitschrift für Psychologie · doi:10.1027/2151-2604/a000260 · Cited by 13
Positive-blank versus negative-blank feedback learning in children and adults
Verburg, M., Snellings, P., Zeguers, M. H. T., & Huizenga, H. M. (2018) · Quarterly Journal of Experimental Psychology · doi:10.1177/1747021818769038 · Cited by 17
Li, F., Wang, J., Du, B., & Cao, B. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.00057 · Cited by 13
Ohira, H., Ichikawa, N., Kimura, K., Fukuyama, S., Shinoda, J., & Yamada, J. (2014) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2014.00381 · Cited by 12
Schaaf, J. V., Jepma, M., Visser, I., & Huizenga, H. M. (2019) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2019.102276 · Cited by 12
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Thomas, L. A., Hall, J. M., Skup, M., Jenkins, S. E., Pine, D. S., & Leibenluft, E. (2010) · Developmental Science · doi:10.1111/j.1467-7687.2010.00967.x · Cited by 11
Laura, V.-P., & Andrei, M. (2020) · University Libraries (University of Maryland) · doi:10.13016/qwmh-khiz · Cited by 10
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Xu, T., Chen, Z., Sirois, F. M., Zhang, R., Yang, Y., & Feng, T. (2020) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00251-z · Cited by 7
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Stelzer, F., Cervigni, M., & Martino, P. (2010) · Americanae (AECID Library) · Cited by 5
Jin, Z., Li, S., Wang, C., Chai, X. J., Zhang, J., & Li, L. (2024) · Brain Topography · doi:10.1007/s10548-024-01094-8 · Cited by 3
Ding, T., Xian, P., Jin, S., Liu, Z., & You, X. (2025) · Human Brain Mapping · doi:10.1002/hbm.70295 · Cited by 3
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Duerden, E. G., Lee, M., Chow, S., Sato, J., Mak‐Fan, K. M., & Taylor, M. J. (2016) · Child Neurology Open · doi:10.1177/2329048x16667350 · Cited by 3
Müller, M., Adámek, P., Kotherová, S., Petrů, M., Bubík, T., Daušová, A., & Pelíšková, L. (2022) · Integrative Psychological and Behavioral Science · doi:10.1007/s12124-022-09719-y · Cited by 3
Ambrasė, A., Müller, V. I., Camilleri, J. A., Wong, H. Y., & Derntl, B. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00277 · Cited by 4
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Tehrani-Safa, A. H., Ghaderi, R., Herasat, M., & Sarabi‐Jamab, A. (2023) · Basic and Clinical Neuroscience Journal · doi:10.32598/bcn.2023.5331.1 · Cited by 2
FMRI Studies of the Adolescent Reward System: The Triadic Model Perspective
Plate, R. C., Richards, J., & Ernst, M. (2015) · Springer eBooks · doi:10.1007/978-3-319-17795-3_8 · Cited by 2
Leijenhorst, L. V., & Crone, E. A. (2009) · Neuropraxis · doi:10.1007/bf03080140 · Cited by 1
Self-citationLee, T. M., Leung, A. W., & Chan, C. C. H. (2007) · Future Neurology · doi:10.2217/14796708.2.2.189 · Cited by 1
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Geier, C. F., Padmanabhan, A., & Luna, B. (2011) · Springer eBooks · doi:10.1007/978-1-4614-0785-0_27 · Cited by 1
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Ding, K. (2018) · Electronic Theses of LMU Munich (Ludwig-Maximilians-Universität München) · doi:10.5282/edoc.24088 · Cited by 1
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Osmont, A., Aïte, A., & Habib, M. (2022) · Wiley eBooks · doi:10.1002/9781394150458.ch5 · Cited by 1
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Aklin, W. M., & Chambers, J. C. (2014) · Springer eBooks · doi:10.1007/978-88-470-5322-9_127
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Geier, C. F., Padmanabhan, A., & Luna, B. (2013) · Springer eBooks · doi:10.1007/978-1-4614-7264-3_32
Yang, J., & Zhang, Q. (2011) · Psychophysiology · doi:10.1111/j.1469-8986.2011.1202.x
Tehrani-Safa, A. H., Ghaderi, R., Herasat, M., & Sarabi‐Jamab, A. (2022) · doi:10.31234/osf.io/75xn4
de la Torre, O. M., Valero‐Cabré, A., Gallardo‐Pujol, D., & Redolar-Ripoll, E. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.22.517525
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Schulte‐Rüther, M., & Weiß, E. O. (2020) · OSF Preprints (OSF Preprints)
Yang, Y.-H., Chen, C.-Y., Chen, S., Yang, L.-X., & Liao, R. (2026) · Behavioural Brain Research · doi:10.1016/j.bbr.2026.116446
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Geier, C. F. (2009) · D-Scholarship@Pitt (University of Pittsburgh)
Metadata
- Authors
- van Leijenhorst, L., Crone, E. A., & Bunge, S. A.
- Affiliations
- Leiden University (NL)
- University of California, Davis (US)
- Venue
- Neuropsychologia
- Publisher
- Elsevier BV
- Published
- 2006-01
- Volume
- 44
- Issue
- 11
- Pages
- 2158-2170
- ISSN
- 0028-3932 (ISSN-L)
- OpenAlex
- W2077931784
- Cited by
- 146
- References
- 82
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 3 · 2023: 2 · 2022: 5 · 2021: 3 · 2020: 6 · 2019: 1 · 2018: 8 · 2017: 4 · 2016: 6 · 2015: 9 · 2014: 15 · 2013: 7 · 2012: 9
- FWCI
- 5.99
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neuropsychologia (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation
- University of California, Davis
- 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 › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Keywords
- risk estimation, feedback processing, gambling task, orbitofrontal cortex, anterior cingulate cortex, dorsolateral prefrontal cortex, ventrolateral prefrontal cortex, medial prefrontal cortex, response conflict, children and adolescents, middle-aged adults, decision making under uncertainty
- MeSH terms
- Adolescent, Adult, Aging, Child, Data Interpretation, Statistical, Feedback, Female, Gyrus Cinguli, Humans, Magnetic Resonance Imaging, Male, Nerve Net, Psychomotor Performance, Risk-Taking, Prefrontal Cortex
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