Academic Journal
Neural representations of dynamical state and trait impulsivity in individuals at risk for internet gaming disorder.
| Τίτλος: | Neural representations of dynamical state and trait impulsivity in individuals at risk for internet gaming disorder. |
|---|---|
| Συγγραφείς: | Zhao H; Faculty of Psychology, MOE Key Laboratory of Cognition and Personality, Southwest University, Chongqing, 400715, China.; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China., Xiao Z; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China., Li S; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China., Liu J; Faculty of Psychology, MOE Key Laboratory of Cognition and Personality, Southwest University, Chongqing, 400715, China. ljl20240108@swu.edu.cn., He Q; Faculty of Psychology, MOE Key Laboratory of Cognition and Personality, Southwest University, Chongqing, 400715, China. heqinghua@swu.edu.cn.; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China. heqinghua@swu.edu.cn. |
| Πηγή: | Molecular psychiatry [Mol Psychiatry] 2026 Aug; Vol. 31 (8), pp. 4645-4654. Date of Electronic Publication: 2026 Apr 02. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Nature Publishing Group Specialist Journals Country of Publication: England NLM ID: 9607835 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1476-5578 (Electronic) Linking ISSN: 13594184 NLM ISO Abbreviation: Mol Psychiatry Subsets: MEDLINE |
| Imprint Name(s): | Publication: 2000- : Houndmills, Basingstoke, UK : Nature Publishing Group Specialist Journals Original Publication: Houndmills, Hampshire, UK ; New York, NY : Stockton Press, c1996- |
| Ιατρικοί όροι (MeSH): | Impulsive Behavior*/physiology , Internet Addiction Disorder*/physiopathology , Internet Addiction Disorder*/diagnostic imaging, Magnetic Resonance Imaging/methods ; Brain/physiopathology ; Brain Mapping/methods ; Behavior, Addictive/physiopathology ; Video Games/psychology ; Humans ; Male ; Female ; Young Adult ; Adult ; Adolescent ; Internet |
| Περίληψη: | Impulsivity is a core symptom across multiple addictive disorders, including internet gaming disorder (IGD), yet its multidimensional nature-particularly the neural basis of state and trait impulsivity in IGD-remains poorly understood. We aimed to elucidate the neural correlates of both impulsivity dimensions and uncover how IGD interacts with the heightened impulsive tendencies. Here we conducted a fMRI study with 87 college students at risk for IGD, employing a modified card-guessing task to capture state impulsivity under a loss decision framework. Modified card-guessing paradigm was applied to assess subjects' state-impulsivity via the loss chasing behavior-the tendency to increase wagers to recover previous losses. Trait impulsivity was assessed using the UPPS-P scale. Another independent cohort (n = 84) with similar IGD profiles was further to validate our finding. Behavioral modelling indicated that state impulsivity, manifesting as the loss chasing behavior (i.e., higher wagers under the loss decision framework), dynamically increased as a function of the loss streaks. Neuroimaging analyses identified key brain regions-such as the right middle frontal gyrus, superior frontal gyrus, striatum, and insula-whose activation during loss feedback predicted subsequent impulsive decisions. These neural signatures of state impulsivity successfully distinguished high-risk IGD individuals. Crucially, resting-state functional connectivity (rs-FC) within these regions not only identified IGD risk but also predicted trait impulsivity. Mediation analysis further demonstrated that IGD's influence on trait impulsivity was indirectly mediated by rs-FC patterns linked to state impulsivity. Our findings elucidate the distinct yet interconnected neural representations of state and trait impulsivity in IGD, underscoring the neurobehavioral continuum linking transient impulsive states to enduring impulsive traits in IGD. (© 2026. The Author(s), under exclusive licence to Springer Nature Limited.) |
| Competing Interests: | Competing interests: The authors report no conflicts with any product mentioned or concept discussed in this article. Ethics declarations: All methods were performed in accordance with the relevant guidelines and regulations. The study protocol and all procedures were approved by the local ethics committees of participating centers. For dataset 1, approval was granted by the human research ethics committee of Southwest University (IRB No. H25043). For dataset 2, approval was granted by the human ethics committee of The Ninth People’s Hospital of Chongqing (IRB No. 2019016). All participants provided written informed consent for study participation, data collection, and data sharing in accordance with the Declaration of Helsinki. No identifiable images from human participants are included in this article, and therefore no separate consent for publication of images was required. |
| References: | Meng S-Q, Cheng J-L, Li Y-Y, Yang X-Q, Zheng J-W, Chang X-W, et al. Global prevalence of digital addiction in general population: A systematic review and meta-analysis. Clin Psychol Rev. 2022;92:102128. (PMID: 3515096510.1016/j.cpr.2022.102128) Yao Y-W, Liu L, Ma S-S, Shi X-H, Zhou N, Zhang J-T, et al. Functional and structural neural alterations in Internet gaming disorder: A systematic review and meta-analysis. Neurosci Biobehav Rev. 2017;83:313–24. (PMID: 2910268610.1016/j.neubiorev.2017.10.029) Brand M, Wegmann E, Stark R, Müller A, Wölfling K, Robbins TW, et al. The Interaction of Person-Affect-Cognition-Execution (I-PACE) model for addictive behaviors: Update, generalization to addictive behaviors beyond internet-use disorders, and specification of the process character of addictive behaviors. Neurosci Biobehav Rev. 2019;104:1–10. (PMID: 3124724010.1016/j.neubiorev.2019.06.032) Bechara A. Decision making, impulse control and loss of willpower to resist drugs: a neurocognitive perspective. Nat Neurosci. 2005;8:1458–63. (PMID: 1625198810.1038/nn1584) Verdejo-García A, Bechara A. A somatic marker theory of addiction. Neuropharmacology. 2009;56:48–62. (PMID: 1872239010.1016/j.neuropharm.2008.07.035) Brand M, Young KS, Laier C, Wölfling K, Potenza MN. Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: An Interaction of Person-Affect-Cognition-Execution (I-PACE) model. Neurosci Biobehav Rev. 2016;71:252–66. (PMID: 2759082910.1016/j.neubiorev.2016.08.033) He Q, Turel O, Brevers D, Bechara A. Excess social media use in normal populations is associated with amygdala-striatal but not with prefrontal morphology. Psychiatry Res: Neuroimaging. 2017;269:31–35. (PMID: 2891826910.1016/j.pscychresns.2017.09.003) Turel O, Bechara A. A triadic reflective-impulsive-interoceptive awareness model of general and impulsive information system use: behavioral tests of neuro-cognitive theory. Front Psychol. 2016;7:601. (PMID: 27199834484551710.3389/fpsyg.2016.00601) Steele JS, Bertocci M, Eckstrand K, Chase HW, Stiffler R, Aslam H, et al. A specific neural substrate predicting current and future impulsivity in young adults. Mol Psychiatry. 2021;26:4919–30. (PMID: 33495543858968310.1038/s41380-021-01017-0) Fineberg NA, Chamberlain SR, Goudriaan AE, Stein DJ, Vanderschuren LJMJ, Gillan CM, et al. New developments in human neurocognition: clinical, genetic, and brain imaging correlates of impulsivity and compulsivity. CNS Spectr. 2014;19:69–89. (PMID: 24512640411333510.1017/S1092852913000801) Morein-Zamir S, Robbins TW. Fronto-striatal circuits in response-inhibition: Relevance to addiction. Brain Res. 2015;1628:117–29. (PMID: 2521861110.1016/j.brainres.2014.09.012) Hüpen P, Habel U, Votinov M, Kable JW, Wagels L. A systematic review on common and distinct neural correlates of risk-taking in substance-related and non-substance related addictions. Neuropsychol Rev. 2023;33:492–513. (PMID: 3590651110.1007/s11065-022-09552-5) Dalley JW, Everitt BJ, Robbins TW. Impulsivity, compulsivity, and top-down cognitive control. Neuron. 2011;69:680–94. (PMID: 2133887910.1016/j.neuron.2011.01.020) Wingrove J, Bond AJ. Impulsivity: A state as well as trait variable. Does mood awareness explain low correlations between trait and behavioural measures of impulsivity? Pers Individ Dif. 1997;22:333–9. (PMID: 10.1016/S0191-8869(96)00222-X) Zermatten A, Van der Linden M, d’Acremont M, Jermann F, Bechara A. Impulsivity and decision making. J Nerv Ment Dis. 2005;193:647–50. (PMID: 1620815910.1097/01.nmd.0000180777.41295.65) Pan N, Wang S, Zhao Y, Lai H, Qin K, Li J, et al. Brain gray matter structures associated with trait impulsivity: a systematic review and voxel-based meta-analysis. Hum Brain Mapp. 2021;42:2214–35. (PMID: 33599347804606210.1002/hbm.25361) Buckholtz JW, Meyer-Lindenberg A. Psychopathology and the human connectome: toward a transdiagnostic model of risk for mental illness. Neuron. 2012;74:990–1004. (PMID: 2272683010.1016/j.neuron.2012.06.002) Zilverstand A, Parvaz MA, Moeller SJ, Kalayci S, Kundu P, Malaker P, et al. Whole-brain resting-state connectivity underlying impaired inhibitory control during early versus longer-term abstinence in cocaine addiction. Mol Psychiatry. 2023;28:3355–64. (PMID: 375282271073199910.1038/s41380-023-02199-5) Davis FC, Knodt AR, Sporns O, Lahey BB, Zald DH, Brigidi BD, et al. Impulsivity and the modular organization of resting-state neural networks. Cereb Cortex. 2013;23:1444–52. (PMID: 2264525310.1093/cercor/bhs126) van Baal ST, Moskovsky N, Hohwy J, Verdejo-García A. State impulsivity amplifies urges without diminishing self-control. Addict Behav. 2022;133:107381. (PMID: 3565969210.1016/j.addbeh.2022.107381) Antons S, Brand M. Trait and state impulsivity in males with tendency towards Internet-pornography-use disorder. Addict Behav. 2018;79:171–7. (PMID: 2929150810.1016/j.addbeh.2017.12.029) Campbell-Meiklejohn DK, Woolrich MW, Passingham RE, Rogers RD. Knowing when to stop: the brain mechanisms of chasing losses. Biol Psychiatry. 2008;63:293–300. (PMID: 1766225710.1016/j.biopsych.2007.05.014) Voon V, Manssuer L, Zhao Y-J, Ding Q, Zhao Y, Wang L, et al. Modeling impulsivity and risk aversion in the subthalamic nucleus with deep brain stimulation. Nat Ment Health. 2024;2:1084–95. (PMID: 392633641138379810.1038/s44220-024-00289-z) Shen X, Finn ES, Scheinost D, Rosenberg MD, Chun MM, Papademetris X, et al. Using connectome-based predictive modeling to predict individual behavior from brain connectivity. Nat Protoc. 2017;12:506–18. (PMID: 28182017552668110.1038/nprot.2016.178) Song K-R, Potenza MN, Fang X-Y, Gong G-L, Yao Y-W, Wang Z-L, et al. Resting-state connectome-based support-vector-machine predictive modeling of internet gaming disorder. Addict Biol. 2021;26:e12969. (PMID: 3304742510.1111/adb.12969) Ni H, Wang H, Ma X, Li S, Liu C, Song X, et al. Efficacy and neural mechanisms of mindfulness meditation among adults with internet gaming disorder: a randomized clinical trial. JAMA Network Open. 2024;7:e2416684–e2416684. (PMID: 388889241118598810.1001/jamanetworkopen.2024.16684) Lynam DR, Miller JD, Miller DJ, Bornovalova MA, Lejuez CW. Testing the relations between impulsivity-related traits, suicidality, and nonsuicidal self-injury: a test of the incremental validity of the UPPS model. Personal Disord: Theory Res Treat. 2011;2:151–60. (PMID: 10.1037/a0019978) Young KS. Internet addiction: the emergence of a new clinical Disorder. Cyberpsychol Behav. 1998;1:237–44. (PMID: 10.1089/cpb.1998.1.237) He J, Tu S, Zhao H, He Q. Transitioning from perceived stress to mental health: The mediating role of self-control in a longitudinal investigation with MRI scans. Int J Clin Health Psychol. 2025;25:100539. (PMID: 398778931177324210.1016/j.ijchp.2024.100539) Wen X, Yue L, Du Z, Zhao J, Ge M, Yuan C, et al. Functional connectome gradient of prefrontal cortex as biomarkers of high risk for internet gaming disorder. Neuroimage. 2025;306:121010. (PMID: 3979883110.1016/j.neuroimage.2025.121010) Huang X, Zhang H, Chen C, Xue G, He Q. The neuroanatomical basis of the Gambler’s fallacy: a univariate and multivariate morphometric study. Hum Brain Mapp. 2019;40:967–75. (PMID: 3031132210.1002/hbm.24425) Xue G, Juan C-H, Chang C-F, Lu Z-L, Dong Q. Lateral prefrontal cortex contributes to maladaptive decisions. Proc Natl Acad Sci. 2012;109:4401–6. (PMID: 22393013331138510.1073/pnas.1111927109) Fan D, Che X, Jiang Y, He Q, Yu J, Zhao H. Noninvasive brain stimulations modulated brain modular interactions to ameliorate working memory in community-dwelling older adults. Cereb Cortex. 2024;34:bhae140. (PMID: 3860273910.1093/cercor/bhae140) Zhao H, Ge M, Turel O, Bechara A, He Q. Brain modular connectivity interactions can predict proactive inhibition in smokers when facing smoking cues. Addict Biol. 2023;28:e13284. (PMID: 3725287810.1111/adb.13284) Frömer R, Dean Wolf CK, Shenhav A. Goal congruency dominates reward value in accounting for behavioral and neural correlates of value-based decision-making. Nat Commun. 2019;10:4926. (PMID: 31664035682073510.1038/s41467-019-12931-x) Kahneman D. A psychological perspective on economics. Am Econ Rev. 2003;93:162–8. (PMID: 10.1257/000282803321946985) Körding K. Decision theory: what “Should” the nervous system do? Science. 2007;318:606–10. (PMID: 1796255410.1126/science.1142998) Ritzwoller DM, Romano JP. Uncertainty in the hot hand fallacy: detecting streaky alternatives to random bernoulli sequences. Rev Econ Stud. 2022;89:976–1007. (PMID: 10.1093/restud/rdab020) Huber J, Kirchler M, Stöckl T. The hot hand belief and the gambler’s fallacy in investment decisions under risk. Theory Decis. 2010;68:445–62. (PMID: 10.1007/s11238-008-9106-2) Kang T, Zhang Y, Zhao J, Li X, Jiang H, Niu X, et al. Characterizing impulsivity in individuals with heroin use disorder. Int J Ment Health Addictn. 2024;22:1530–45. (PMID: 10.1007/s11469-022-00941-8) Jiang K, Zhao G, Feng Q, Guan S, Im H, Zhang B, et al. The computational and neural substrates of individual differences in impulsivity under loss framework. Hum Brain Mapp. 2024;45:e26808. (PMID: 391263471131624810.1002/hbm.26808) Balodis IM, Kober H, Worhunsky PD, Stevens MC, Pearlson GD, Potenza MN. Diminished frontostriatal activity during processing of monetary rewards and losses in pathological gambling. Biol Psychiatry. 2012;71:749–57. (PMID: 22336565346052210.1016/j.biopsych.2012.01.006) Pujara MS, Philippi CL, Motzkin JC, Baskaya MK, Koenigs M. Ventromedial prefrontal cortex damage is associated with decreased ventral striatum volume and response to reward. J Neurosci. 2016;36:5047. (PMID: 27147657485496710.1523/JNEUROSCI.4236-15.2016) Jocham G, Klein TA, Ullsperger M. Dopamine-mediated reinforcement learning signals in the striatum and ventromedial prefrontal cortex underlie value-based choices. J Neurosci. 2011;31:1606. (PMID: 21289169662374910.1523/JNEUROSCI.3904-10.2011) Corradi-Dell’Acqua C, Tusche A, Vuilleumier P, Singer T. Cross-modal representations of first-hand and vicarious pain, disgust and fairness in insular and cingulate cortex. Nat Commun. 2016;7:10904. (PMID: 26988654480203310.1038/ncomms10904) Yang Y-P, Li X, Stuphorn V. Primate anterior insular cortex represents economic decision variables proposed by prospect theory. Nat Commun. 2022;13:717. (PMID: 35132070882171510.1038/s41467-022-28278-9) Pearson JM, Heilbronner SR, Barack DL, Hayden BY, Platt ML. Posterior cingulate cortex: adapting behavior to a changing world. Trends Cogn Sci. 2011;15:143–51. (PMID: 21420893307078010.1016/j.tics.2011.02.002) Xue G, Lu Z, Levin IP, Bechara A. The impact of prior risk experiences on subsequent risky decision-making: the role of the insula. Neuroimage. 2010;50:709–16. (PMID: 20045470282804010.1016/j.neuroimage.2009.12.097) Drummond N, Niv Y. Model-based decision making and model-free learning. Curr Biol. 2020;30:R860–R865. (PMID: 3275034010.1016/j.cub.2020.06.051) Smittenaar P, FitzGerald THB, Romei V, Wright ND, Dolan RJ. Disruption of dorsolateral prefrontal cortex decreases model-based in favor of model-free control in humans. Neuron. 2013;80:914–9. (PMID: 24206669389345410.1016/j.neuron.2013.08.009) Dixon ML, Christoff K. The lateral prefrontal cortex and complex value-based learning and decision making. Neurosci Biobehav Rev. 2014;45:9–18. (PMID: 2479223410.1016/j.neubiorev.2014.04.011) Hall SA, Towe SL, Nadeem MT, Hobkirk AL, Hartley BW, Li R, et al. Hypoactivation in the precuneus and posterior cingulate cortex during ambiguous decision making in individuals with HIV. J Neurovirol. 2021;27:463–75. (PMID: 33983505827627510.1007/s13365-021-00981-1) Huang Y, Yaple ZA, Yu R. Goal-oriented and habitual decisions: Neural signatures of model-based and model-free learning. Neuroimage. 2020;215:116834. (PMID: 3228327510.1016/j.neuroimage.2020.116834) Kreek MJ, Nielsen DA, Butelman ER, LaForge KS. Genetic influences on impulsivity, risk taking, stress responsivity and vulnerability to drug abuse and addiction. Nat Neurosci. 2005;8:1450–7. (PMID: 1625198710.1038/nn1583) Hu Y, Salmeron BJ, Gu H, Stein EA, Yang Y. Impaired functional connectivity within and between frontostriatal circuits and its association with compulsive drug use and trait impulsivity in cocaine addiction. JAMA Psychiatry. 2015;72:584–92. (PMID: 2585390110.1001/jamapsychiatry.2015.1) Hu Y, Salmeron BJ, Krasnova IN, Gu H, Lu H, Bonci A, et al. Compulsive drug use is associated with imbalance of orbitofrontal- and prelimbic-striatal circuits in punishment-resistant individuals. Proc Natl Acad Sci. 2019;116:9066–71. (PMID: 30988198650016610.1073/pnas.1819978116) Goldstein RZ, Volkow ND. Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications. Nat Rev Neurosci. 2011;12:652–69. (PMID: 22011681346234210.1038/nrn3119) Zha R, Tao R, Kong Q, Li H, Liu Y, Huang R, et al. Impulse control differentiates Internet gaming disorder from non-disordered but heavy Internet gaming use: evidence from multiple behavioral and multimodal neuroimaging data. Comput Human Behav. 2022;130:107184. (PMID: 10.1016/j.chb.2022.107184) Chang MLY, Lee IO. Functional connectivity changes in the brain of adolescents with internet addiction: a systematic literature review of imaging studies. PLOS Mental Health. 2024;1:e0000022. (PMID: 416618251279830510.1371/journal.pmen.0000022) Huang X, Qi Y, Zhang R, Pu Y, Chen X, Chen S, et al. Altered executive control network and default model network topology are linked to acute electronic cigarette use: A resting-state fNIRS study. Addict Biol. 2024;29:e13423. (PMID: 389492051121579010.1111/adb.13423) Li L, Li LMW, Ma J, Lu A, Dai Z. The relationship between personality traits and well-being via brain functional connectivity. J Happiness Stud. 2023;24:2127–52. (PMID: 10.1007/s10902-023-00674-y) Hardikar S, McKeown B, Turnbull A, Xu T, Valk SL, Bernhardt BC, et al. Personality traits vary in their association with brain activity across situations. Commun Biol. 2024;7:1498. (PMID: 395330851155789410.1038/s42003-024-07061-0) Stendel MS, Chavez RS. Beyond the brain localization of complex traits: Distributed white matter markers of personality. J Pers. 2023;91:1140–51. (PMID: 3627327610.1111/jopy.12788) Liu W, Kohn N, Fernández G. Intersubject similarity of personality is associated with intersubject similarity of brain connectivity patterns. Neuroimage. 2019;186:56–69. (PMID: 3038963010.1016/j.neuroimage.2018.10.062) Ren Z, Sun J, Liu C, Li X, Li X, Li X, et al. Individualized prediction of trait self-control from whole-brain functional connectivity. Psychophysiology. 2023;60:e14209. (PMID: 3632562610.1111/psyp.14209) Angelides NH, Gupta J, Vickery TJ. Associating resting-state connectivity with trait impulsivity. Soc Cogn Affect Neurosci. 2017;12:1001–8. (PMID: 28402539547212510.1093/scan/nsx031) Hüpen P, Kumar H, Müller D, Swaminathan R, Habel U, Weidler C. Functional brain network of trait impulsivity: whole-brain functional connectivity predicts self-reported impulsivity. Hum Brain Mapp. 2024;45:e70059. (PMID: 394698911151974710.1002/hbm.70059) Sharma L, Markon KE, Clark LA. Toward a theory of distinct types of “impulsive” behaviors: a meta-analysis of self-report and behavioral measures. Psychol Bull. 2014;140:374–408. (PMID: 2409940010.1037/a0034418) Knezevic-Budisin B, Pedden V, White A, Miller CJ, Hoaken PNS. A Multifactorial conceptualization of impulsivity. J Individ Differ. 2015;36:191–8. (PMID: 10.1027/1614-0001/a000173) Wilbertz T, Deserno L, Horstmann A, Neumann J, Villringer A, Heinze H-J, et al. Response inhibition and its relation to multidimensional impulsivity. Neuroimage. 2014;103:241–8. (PMID: 2524108710.1016/j.neuroimage.2014.09.021) Maxwell SE, Cole DA. Bias in cross-sectional analyses of longitudinal mediation. Psychol Methods. 2007;12:23–44. (PMID: 1740281010.1037/1082-989X.12.1.23) Huang Y, Luan S, Wu B, Li Y, Wu J, Chen W, et al. Impulsivity is a stable, measurable, and predictive psychological trait. Proc Natl Acad Sci. 2024;121:e2321758121. (PMID: 388300931118111410.1073/pnas.2321758121) |
| Grant Information: | 31972906 National Natural Science Foundation of China (National Science Foundation of China); 32300859 National Natural Science Foundation of China (National Science Foundation of China); 2023NSCQ-MSX0899 Natural Science Foundation of Chongqing (Natural Science Foundation of Chongqing Municipality) |
| Entry Date(s): | Date Created: 20260402 Date Completed: 20260714 Latest Revision: 20260714 |
| Update Code: | 20260714 |
| DOI: | 10.1038/s41380-026-03589-1 |
| PMID: | 41927766 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1476-5578 |
|---|---|
| DOI: | 10.1038/s41380-026-03589-1 |