Reward Processing in Novelty Seekers: A Transdiagnostic Psychiatric Imaging Biomarker
Open accessAbstract
BACKGROUND: Dysfunctional reward processing is implicated in multiple mental disorders. Novelty seeking (NS) assesses preference for seeking novel experiences, which is linked to sensitivity to reward environmental cues. METHODS: A subset of 14-year-old adolescents (IMAGEN) with the top 20% ranked high-NS scores was used to identify high-NS–associated multimodal components by supervised fusion. These features were then used to longitudinally predict five different risk scales for the same and unseen subjects (an independent dataset of subjects at 19 years of age that was not used in predictive modeling training at 14 years of age) (within IMAGEN, n ≈ 1100) and even for the corresponding symptom scores of five types of patient cohorts (non-IMAGEN), including drinking (n = 313), smoking (n = 104), attention-deficit/hyperactivity disorder (n = 320), major depressive disorder (n = 81), and schizophrenia (n = 147), as well as to classify different patient groups with diagnostic labels. RESULTS: Multimodal biomarkers, including the prefrontal cortex, striatum, amygdala, and hippocampus, associated with high NS in 14-year-old adolescents were identified. The prediction models built on these features are able to longitudinally predict five different risk scales, including alcohol drinking, smoking, hyperactivity, depression, and psychosis for the same and unseen 19-year-old adolescents and even predict the corresponding symptom scores of five types of patient cohorts. Furthermore, the identified reward-related multimodal features can classify among attention-deficit/hyperactivity disorder, major depressive disorder, and schizophrenia with an accuracy of 87.2%. CONCLUSIONS: Adolescents with higher NS scores can be used to reveal brain alterations in the reward-related system, implicating potential higher risk for subsequent development of multiple disorders. The identified high-NS–associated multimodal reward-related signatures may serve as a transdiagnostic neuroimaging biomarker to predict disease risks or severity.
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Symptoms of neurodevelopmental disorders may be driven by alterations in both brain structure and function.
“Moreover, typical symptoms presented in neurodevelopmental disorders might be driven by alterations of both brain structure and function [48, 49].”
From Confound Controlled Multimodal Neuroimaging Data Fusion and Its Application to Developmental Disorders (2025) · cites this paper as [49]
The Methods describe both gray-matter volume and functional MRI measures, and the Conclusions say the resulting network features predict symptom severity in the studied clinical groups, including ADHD. The paper does not establish that structural and functional alterations drive symptoms across neurodevelopmental disorders generally; its evidence is predictive and spans several psychiatric conditions. (LLM, conf=0.84)
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“Moreover, typical symptoms presented in neurodevelopmental disorders might be driven by alterations of both brain structure and function [48], [49].”
Self-citation
- Authors
- Qi, S., Schumann, G., Bustillo, J., Turner, J. A., Jiang, R., Zhi, D., Fu, Z., Mayer, A. R., Vergara, V. M., Silva, R. F., Iraji, A., Chen, J., Damaraju, E., Ma, X., Yang, X., Stevens, M., Mathalon, D. H., Ford, J. M., Voyvodic, J., Mueller, B. A., Belger, A., Potkin, S. G., Preda, A., Zhuo, C., Xu, Y., Chu, C., Banaschewski, T., Barker, G. J., Bokde, A. L. W., Quinlan, E. B., Desrivières, S., Flor, H., Grigis, A., Garavan, H., Gowland, P., Heinz, A., Martinot, J.-L., Paillère Martinot, M.-L., Artiges, E., Nees, F., Orfanos, D. P., Paus, T., Poustka, L., Hohmann, S., Fröhner, J. H., Smolka, M. N., Walter, H., Whelan, R., Calhoun, V. D., Sui, J., Schumann, G., Banaschewski, T., Barker, G. J., Bokde, A. L. W., Quinlan, E. B., Desrivières, S., Flor, H., Grigis, A., Garavan, H., Gowland, P., Heinz, A., Martinot, J.-L., Paillère Martinot, M.-L., Artiges, E., Nees, F., Orfanos, D. P., Paus, T., Poustka, L., Hohmann, S., Fröhner, J. H., Smolka, M. N., Walter, H., & Whelan, R.
- Affiliations
- Georgia Institute of Technology (US)
- University of New Mexico (US)
- Georgia State University (US)
- Chinese Academy of Sciences (CN)
- Sichuan University (CN)
- University of California, San Francisco (US)
- Duke University (US)
- University of Minnesota (US)
- University of California, Irvine (US)
- Nankai University (CN)
- Shanxi Medical University (CN)
- Fudan University (CN)
- Corresponding author
- Calhoun, Vince D.
- ORCID
- Qi, Shile
- Bustillo, Juan
- Turner, Jessica A.
- Jiang, Rongtao
- Zhi, Dongmei
- Fu, Zening
- Mayer, Andrew R.
- Vergara, Victor M.
- Silva, Rogers F.
- Iraji, Armin
- Chen, Jiayu
- Damaraju, Eswar
- Ma, Xiaohong
- Yang, Xiao
- Stevens, Michael
- Mathalon, Daniel H.
- Ford, Judith M.
- Voyvodic, James
- Mueller, Bryon A.
- Potkin, Steven G.
- Preda, Adrian
- Zhuo, Chuanjun
- Xu, Yong
- Chu, Congying
- Calhoun, Vince D.
- Venue
- Biological Psychiatry
- Publisher
- Elsevier BV
- Published
- 2021-10
- Volume
- 90
- Issue
- 8
- Pages
- 529-539
- ISSN
- 0006-3223 (ISSN-L)
- PMC
- PMC8322149
- OpenAlex
- W3128947369
- Semantic Scholar
- 4513bfa57839ca2b6102cdcb14433fbfef935186
- Cited by
- 55
- References
- 61
- Citations by year
- 2026: 5 · 2025: 14 · 2024: 10 · 2023: 9 · 2022: 12 · 2021: 5
- FWCI
- 4.73
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Biological Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- HAL (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen) (submittedVersion, cc-by)
- Funders
- National Science Foundation (1539067)
- EU Joint Programme – Neurodegenerative Disease Research (785907, MR/N027558/1)
- Fondation pour la Recherche Médicale
- National Institutes of Health (1R56AG058854-01, 5U54EB020403-05, P20GM103472, P30GM122734, R01EB005846, R01MH117107)
- Fondation de France
- King’s College London
- Seventh Framework Programme (603016)
- Sixth Framework Programme (LSHM-CT-2007-037286)
- Horizon 2020 (695313)
- Beijing Municipal Science and Technology Commission (Z181100001518005)
- Deutsche Forschungsgemeinschaft (NE 1383/14-1, SFB 940/2, SM 80/7-2)
- Medical Research Council (MR/N000390/1)
- King's College London
- European Commission
- Science Foundation Ireland (16/ERCD/3797)
- Institut National de la Santé et de la Recherche Médicale
- National Natural Science Foundation of China (61773380, 82022035)
- Bundesministerium für Bildung und Forschung (01EE1406A, 01EE1406B, 01EV0711, 01GS08152)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Keywords
- novelty seeking, reward processing, transdiagnostic biomarkers, adolescents, multimodal neuroimaging, alcohol consumption, smoking, attention deficit hyperactivity disorder, major depressive disorder, schizophrenia, psychosis, prefrontal cortex, striatum, amygdala, hippocampus, mental illness
- MeSH terms
- Adolescent, Adult, Attention Deficit Disorder with Hyperactivity, Major Depressive Disorder, Humans, Magnetic Resonance Imaging, Reward, Biomarkers, Young Adult
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 ›
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