Adolescence is a critical period of neurocognitive development and increased prevalence of mood pathology. In this cross-sectional study, we replicated developmental patterns of neurocognition and tested whether mood symptoms moderated developmental effects. Participants were 419 adolescents (n = 246 with current mood disorders) who completed reward-learning and executive-functioning tasks and reported on age, puberty, and mood symptoms. Structural equation modeling revealed a quadratic relationship between puberty and reward-learning performance that was moderated by symptom severity: In early puberty, adolescents reporting higher manic symptoms exhibited heightened reward-learning performance (better maximizing of rewards on learning tasks), whereas adolescents reporting elevated anhedonia showed blunted reward-learning performance. Models also showed a linear relationship between age and executive functioning that was moderated by manic symptoms: Adolescents reporting higher mania showed poorer executive functioning at older ages. Findings suggest neurocognitive development is altered in adolescents with mood pathology and suggest directions for longitudinal studies.
AlloyL. B.NusslockR. (2019). Future directions for understanding adolescent bipolar spectrum disorders: A reward hypersensitivity perspective. Journal of Clinical Child & Adolescent Psychology, 48(4), 669–683. https://doi.org/10.1080/15374416.2019.1567347
2.
AlloyL. B.OlinoT.FreedR. D.NusslockR. (2016). Role of reward sensitivity and processing in major depressive and bipolar spectrum disorders. Behavior Therapy, 47(5), 600–621. https://doi.org/10.1016/j.beth.2016.02.014
3.
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.).
4.
Ayuso-MateosJ. L.NuevoR.VerdesE.NaidooN.ChatterjiS. (2010). From depressive symptoms to depressive disorders: The relevance of thresholds. British Journal of Psychiatry, 196(5), 365–371. https://doi.org/10.1192/bjp.bp.109.071191
5.
BarchD. M.AlbaughM. D.AvenevoliS.ChangL.ClarkD. B.GlantzM. D.HudziakJ. J.JerniganT. L.TapertS. F.Yurgelun-ToddD.Alia-KleinN.PotterA. S.PaulusM. P.ProutyD.ZuckerR. A.SherK. J. (2018). Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: Rationale and description. Developmental Cognitive Neuroscience, 32, 55–66. https://doi.org/10.1016/j.dcn.2017.10.010
BirmaherB.AxelsonD. (2006). Course and outcome of bipolar spectrum disorder in children and adolescents: A review of the existing literature. Development and Psychopathology, 18(4). https://doi.org/10.1017/S0954579406060500
10.
BiuckiansA.MiklowitzD. J.KimE. Y. (2007). Behavioral activation, inhibition and mood symptoms in early-onset bipolar disorder. Journal of Affective Disorders, 97(1–3), 71–76. https://doi.org/10.1016/j.jad.2006.07.005
11.
BlakemoreS.-J.BurnettS.DahlR. E. (2010). The role of puberty in the developing adolescent brain. Human Brain Mapping, 31(6), 926–933. https://doi.org/10.1002/hbm.21052
12.
BraamsB. R.van DuijvenvoordeA. C. K.PeperJ. S.CroneE. A. (2015). Longitudinal changes in adolescent risk-taking: A comprehensive study of neural responses to rewards, pubertal development, and risk-taking behavior. The Journal of Neuroscience, 35(18), 7226–7238. https://doi.org/10.1523/JNEUROSCI.4764-14.2015
13.
CaseyB. J.JonesR. M.HareT. A. (2008). The adolescent brain. Annals of the New York Academy of Sciences, 1124, 111–126. https://doi.org/10.1196/annals.1440.010
14.
CollinsA. G. E.FrankM. J. (2012). How much of reinforcement learning is working memory, not reinforcement learning? A behavioral, computational, and neurogenetic analysis: Working memory in reinforcement learning. European Journal of Neuroscience, 35(7), 1024–1035. https://doi.org/10.1111/j.1460-9568.2011.07980.x
15.
CopelandW. E.WolkeD.ShanahanL.CostelloE. J. (2015). Adult functional outcomes of common childhood psychiatric problems: A prospective, longitudinal study. JAMA Psychiatry, 72(9), 892–899. https://doi.org/10.1001/jamapsychiatry.2015.0730
DavidowJ. Y.FoerdeK.GalvánA.ShohamyD. (2016). An upside to reward sensitivity: The hippocampus supports enhanced reinforcement learning in adolescence. Neuron, 92(1), 93–99. https://doi.org/10.1016/j.neuron.2016.08.031
18.
DawN. (2011). Trial-by-trial data analysis using computational models. In DelgadoM. R.PhelpsE. A.RobbinsT. W. (Eds.), Decision making, affect, and learning: Attention and performance XXIII (pp. 3–37). Oxford University Press.
19.
DelevichK.KlingerM.OkadaN. J.WilbrechtL. (2021). Coming of age in the frontal cortex: The role of puberty in cortical maturation. Seminars in Cell & Developmental Biology, 118, 64–72. https://doi.org/10.1016/j.semcdb.2021.04.021
20.
DepueR. A.KraussS.SpoontM. R.ArbisiP. (1989). General behavior inventory identification of unipolar and bipolar affective conditions in a nonclinical university population. Journal of Abnormal Psychology, 98(2), 117–126.
21.
Der-AvakianA.BarnesS. A.MarkouA.PizzagalliD. A. (2016). Translational assessment of reward and motivational deficits in psychiatric disorders. Current Topics in Behavioral Neurosciences, 28, 231–262. https://doi.org/10.1007/7854_2015_5004
22.
DixonT.KravaritiE.FrithC.MurrayR. M.McGuireP. K. (2004). Effect of symptoms on executive function in bipolar illness. Psychological Medicine, 34(5), 811–821. https://doi.org/10.1017/S0033291703001570
23.
ForbesE. E.DahlR. E. (2010). Pubertal development and behavior: Hormonal activation of social and motivational tendencies. Brain and Cognition, 72(1), 66–72. https://doi.org/10.1016/j.bandc.2009.10.007
24.
ForbesE. E.DahlR. E. (2012). Research Review: Altered reward function in adolescent depression: What, when and how? Reward function and adolescent depression. Journal of Child Psychology and Psychiatry, 53(1), 3–15. https://doi.org/10.1111/j.1469-7610.2011.02477.x
25.
ForbesE. E.EckstrandK. L.RofeyD. L.SilkJ. S. (2021). A social affective neuroscience model of risk and resilience in adolescent depression: Preliminary evidence and application to sexual and gender minority adolescents. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 6(2), 188–199. https://doi.org/10.1016/j.bpsc.2020.07.020
26.
FrankM. J.MoustafaA. A.HaugheyH. M.CurranT.HutchisonK. E. (2007). Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learning. Proceedings of the National Academy of Sciences, USA, 104(41), 16311–16316. https://doi.org/10.1073/pnas.0706111104
27.
FriedmanN. P.du PontA.CorleyR. P.HewittJ. K. (2018). Longitudinal relations between depressive symptoms and executive functions from adolescence to early adulthood: A twin study. Clinical Psychological Science, 6(4), 543–560. https://doi.org/10.1177/2167702618766360
28.
FriedmanN. P.MiyakeA. (2017). Unity and diversity of executive functions: Individual differences as a window on cognitive structure. Cortex, 86, 186–204. https://doi.org/10.1016/j.cortex.2016.04.023
29.
FriedmanN. P.MiyakeA.AltamiranoL. J.CorleyR. P.YoungS. E.RheaS. A.HewittJ. K. (2016). Stability and change in executive function abilities from late adolescence to early adulthood: A longitudinal twin study. Developmental Psychology, 52(2), 326–340. https://doi.org/10.1037/dev0000075
30.
FriedmanN. P.MiyakeA.YoungS. E.DeFriesJ. C.CorleyR. P.HewittJ. K. (2008). Individual differences in executive functions are almost entirely genetic in origin. Journal of Experimental Psychology-General, 137(2), 201–225. https://doi.org/10.1037/0096-3445.137.2.201
31.
GaffreyM. S.LubyJ. L.BarchD. M. (2013). Towards the study of functional brain development in depression: An Interactive Specialization approach. Neurobiology of Disease, 52, 38–48. https://doi.org/10.1016/j.nbd.2012.06.012
GeierC.LunaB. (2009). The maturation of incentive processing and cognitive control. Pharmacology, Biochemistry, and Behavior, 93(3), 212–221. https://doi.org/10.1016/j.pbb.2009.01.021
34.
HairJ. F. (Ed.). (2010). Multivariate data analysis (7th ed.). Prentice Hall.
35.
HardenK. P.MannF. D.GrotzingerA. D.PattersonM. W.SteinbergL.TackettJ. L.Tucker-DrobE. M. (2018). Developmental differences in reward sensitivity and sensation seeking in adolescence: Testing sex-specific associations with gonadal hormones and pubertal development. Journal of Personality and Social Psychology, 115(1), 161–178. https://doi.org/10.1037/pspp0000172
36.
HornK.RoessnerV.HoltmannM. (2011). Neurocognitive performance in children and adolescents with bipolar disorder: A review. European Child & Adolescent Psychiatry, 20(9), 433–450. https://doi.org/10.1007/s00787-011-0209-x
JohnsonJ. M.NachtigallL. B.SternT. A. (2013). The effect of testosterone levels on mood in men: A review. Psychosomatics, 54(6), 509–514. https://doi.org/10.1016/j.psym.2013.06.018
39.
JosephM. F.FrazierT. W.YoungstromE. A.SoaresJ. C. (2008). A quantitative and qualitative review of neurocognitive performance in pediatric bipolar disorder. Journal of Child and Adolescent Psychopharmacology, 18(6), 595–605. https://doi.org/10.1089/cap.2008.064
40.
KesslerR. C.BerglundP.DemlerO.JinR.MerikangasK. R.WaltersE. E. (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62(6), 593–602. https://doi.org/10.1001/archpsyc.62.6.593
41.
KlineR. B. (2011). Principles and practice of structural equation modeling (3rd ed.). The Guilford Press.
42.
KujawaA.KleinD. N.PeggS.WeinbergA. (2020). Developmental trajectories to reduced activation of positive valence systems: A review of biological and environmental contributions. Developmental Cognitive Neuroscience, 43, Article 100791. https://doi.org/10.1016/j.dcn.2020.100791
43.
LawlorV. M.WebbC. A.WieckiT. V.FrankM. J.TrivediM.PizzagalliD. A.DillonD. G. (2020). Dissecting the impact of depression on decision-making. Psychological Medicine, 50(10), 1613–1622. https://doi.org/10.1017/S0033291719001570
44.
LeeR. S. C.HermensD. F.ScottJ.Redoblado-HodgeM. A.NaismithS. L.LagopoulosJ.GriffithsK. R.PorterM. A.HickieI. B. (2014). A meta-analysis of neuropsychological functioning in first-episode bipolar disorders. Journal of Psychiatric Research, 57, 1–11. https://doi.org/10.1016/j.jpsychires.2014.06.019
45.
LimaI. M. M.PeckhamA. D.JohnsonS. L. (2018). Cognitive deficits in bipolar disorders: Implications for emotion. Clinical Psychology Review, 59, 126–136. https://doi.org/10.1016/j.cpr.2017.11.006
46.
LombardoG.MondelliV.DazzanP.ParianteC. M. (2021). Sex hormones and immune system: A possible interplay in affective disorders? A systematic review. Journal of Affective Disorders, 290, 1–14. https://doi.org/10.1016/j.jad.2021.04.035
47.
LunaB.MarekS.LarsenB.Tervo-ClemmensB.ChahalR. (2015). An integrative model of the maturation of cognitive control. Annual Review of Neuroscience, 38(1), 151–170. https://doi.org/10.1146/annurev-neuro-071714-034054
48.
LunaB.WrightC. (2016). Adolescent brain development: Implications for the juvenile criminal justice system. In HeilbrunK.DeMatteoD.GoldsteinN. E. S. (Eds.), APA handbook of psychology and juvenile justice (pp. 91–116). American Psychological Association. https://doi.org/10.1037/14643-005
49.
MareshE. L.StimJ. J.Van VoorhisA. C.KangS. S.LucianaM.SponheimS. R.UroševićS. (2019). Neurophysiological correlates of cognitive control and approach motivation abnormalities in adolescent bipolar disorders. Cognitive, Affective, & Behavioral Neuroscience, 19(3), 677–691. https://doi.org/10.3758/s13415-019-00719-x
50.
MasterS. L.EcksteinM. K.GotliebN.DahlR.WilbrechtL.CollinsA. G. E. (2020). Distentangling the systems contributing to changes in learning during adolescence. Developmental Cognitive Neuroscience, 41, Article 100732. https://doi.org/10.1016/j.dcn.2019.100732
51.
McCarthyD.DavisonM. (1979). Signal probability, reinforcement, and signal detection. Journal of the Experimental Analysis of Behavior, 32, 373–386.
52.
McIntyreR. S.SoczynskaJ. K.ChaD. S.WoldeyohannesH. O.DaleR. S.AlsuwaidanM. T.GallaugherL. A.MansurR. B.MuzinaD. J.CarvalhoA.KennedyS. H. (2015). The prevalence and illness characteristics of DSM-5-defined “mixed feature specifier” in adults with major depressive disorder and bipolar disorder: Results from the International Mood Disorders Collaborative Project. Journal of Affective Disorders, 172, 259–264. https://doi.org/10.1016/j.jad.2014.09.026
53.
MendleJ. (2014). Why puberty matters for psychopathology. Child Development Perspectives, 8(4), 218–222. https://doi.org/10.1111/cdep.12092
54.
MiyakeA.FriedmanN. P.EmersonM. J.WitzkiA. H.HowerterA.WagerT. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41(1), 49–100. https://doi.org/10.1006/cogp.1999.0734
55.
MoriarityD. P.NgT.TitoneM. K.ChatI. K.-Y.NusslockR.MillerG. E.AlloyL. B. (2020). Reward responsiveness and ruminative styles interact to predict inflammation and mood symptomatology. Behavior Therapy, 51(5), 829–842. https://doi.org/10.1016/j.beth.2019.11.007
56.
MuthénL. K.MuthénB. O. (2017). Mplus user’s guide (8th ed.).
57.
NielsonD. M.KerenH.O’CallaghanG.JacksonS. M.DoukaI.ZhengC. Y.Vidal-RibasP.PornpattananangkulN.CampC. C.GorhamL. S.WeiC.KirwanS.StringarisA. (2021). Great expectations: A critical review of and recommendations for the study of reward processing as a cause and predictor of depression. Biological Psychiatry, 89(2), P134–P143. https://doi.org/10.1016/j.biopsych.2020.06.012
58.
NussenbaumK.HartleyC. A. (2019). Reinforcement learning across development: What insights can we draw from a decade of research?Developmental Cognitive Neuroscience, 40, Article 100733. https://doi.org/10.1016/j.dcn.2019.100733
59.
NusslockR.AlloyL. B. (2017). Reward processing and mood-related symptoms: An RDoC and translational neuroscience perspective. Journal of Affective Disorders, 216, 3–16. https://doi.org/10.1016/j.jad.2017.02.001
60.
NusslockR.AlmeidaJ. R.ForbesE. E.VersaceA.FrankE.LaBarbaraE. J.KleinC. R.PhillipsM. L. (2012). Waiting to win: Elevated striatal and orbitofrontal cortical activity during reward anticipation in euthymic bipolar disorder adults. Bipolar Disorders, 14(3), 249–260. https://doi.org/10.1111/j.1399-5618.2012.01012.x
61.
PausT.KeshavanM.GieddJ. N. (2008). Why do many psychiatric disorders emerge during adolescence?Nature Reviews Neuroscience, 9(12), 947–957. https://doi.org/10.1038/nrn2513
62.
PetersenA. C.CrockettL.RichardsM.BoxerA. (1988). A self-report measure of pubertal status: Reliability, validity, and initial norms. Journal of Youth and Adolescence, 17(2), 117–133. https://doi.org/10.1007/BF01537962
63.
PhillipsM. L.SwartzH. A. (2014). A critical appraisal of neuroimaging studies of bipolar disorder: Toward a new conceptualization of underlying neural circuitry and a road map for future research. American Journal of Psychiatry, 171(8), 829–843. https://doi.org/10.1176/appi.ajp.2014.13081008
PizzagalliD. A.GoetzE.OstacherM.IosifescuD. V.PerlisR. H. (2008). Euthymic patients with bipolar disorder show decreased reward learning in a probabilistic reward task. Biological Psychiatry, 64(2), 162–168. https://doi.org/10.1016/j.biopsych.2007.12.001
66.
PizzagalliD. A.JahnA. L.O’SheaJ. P. (2005). Toward an objective characterization of an anhedonic phenotype: A signal detection approach. Biological Psychiatry, 57(4), 319–327. https://doi.org/10.1016/j.biopsych.2004.11.026
67.
RescorlaR.WagnerA. (1972). A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. In BlackA. H.ProkasyW. F. (Eds.), Classical conditioning: Current research and theory (pp. 64–99). Appleton-Century.
68.
ReyesA. N.CardosoT. A.JansenK.MondinT. C.SouzaL. D. M.MagalhãesP. V. S.KapczinskiF.SilvaR. A. (2017). Functional impairment and cognitive performance in mood disorders: A community sample of young adults. Psychiatry Research, 251, 85–89. https://doi.org/10.1016/j.psychres.2017.01.069
69.
RobinsonO.ChaseH. (2017). Learning and choice in mood disorders: Searching for the computational parameters of anhedonia. Computational Psychiatry, 1, 208–233. https://doi.org/10.1162/CPSY_a_00009
70.
RockP. L.RoiserJ. P.RiedelW. J.BlackwellA. D. (2014). Cognitive impairment in depression: A systematic review and meta-analysis. Psychological Medicine, 44(10), 2029–2040. https://doi.org/10.1017/S0033291713002535
71.
SarapasC.ShankmanS. A.HarrowM.GoldbergJ. F. (2012). Parsing trait and state effects of depression severity on neurocognition: Evidence from a 26-year longitudinal study. Journal of Abnormal Psychology, 121(4), 830–837. https://doi.org/10.1037/a0028141
72.
SatorraA. (2000). Scaled and adjusted restricted tests in multi-sample analysis of moment structures. In HeijmansR. D. H.PollockD. S. G.SatorraA. (Eds.), Innovations in multivariate statistical analysis. A Festschrift for Heinz Neudecker (pp. 223–247). Kluwer Academic Publishers.
73.
ScultM. A.PaulliA. R.MazureE. S.MoffittT. E.HaririA. R.StraumanT. J. (2017). The association between cognitive function and subsequent depression: A systematic review and meta-analysis. Psychological Medicine, 47(1), 1–17. https://doi.org/10.1017/S0033291716002075
74.
ShirtcliffE. A.DahlR. E.PollakS. D. (2009). Pubertal development: Correspondence between hormonal and physical development: Hormonal correlates of pubertal stage. Child Development, 80(2), 327–337. https://doi.org/10.1111/j.1467-8624.2009.01263.x
75.
ShulmanE. P.SmithA. R.SilvaK.IcenogleG.DuellN.CheinJ.SteinbergL. (2016). The dual systems model: Review, reappraisal, and reaffirmation. Developmental Cognitive Neuroscience, 17, 103–117. https://doi.org/10.1016/j.dcn.2015.12.010
76.
SnyderH. R. (2013). Major Depressive Disorder is associated with broad impairments on neuropsychological measures of executive function: A meta-analysis and review. Psychological Bulletin, 139(1), 81–132. https://doi.org/10.1037/a0028727
77.
SnyderH. R.MiyakeA.HankinB. L. (2015). Advancing understanding of executive function impairments and psychopathology: Bridging the gap between clinical and cognitive approaches. Frontiers in Psychology, 6, Article 24. https://doi.org/10.3389/fpsyg.2015.00728
78.
SteinbergL.AlbertD.CauffmanE.BanichM.GrahamS.WoolardJ. (2008). Age differences in sensation seeking and impulsivity as indexed by behavior and self-report: Evidence for a dual systems model. Developmental Psychology, 44(6), 1764–1778. https://doi.org/10.1037/a0012955
79.
UroševićS.LucianaM.JensenJ. B.YoungstromE. A.ThomasK. M. (2016). Age associations with neural processing of reward anticipation in adolescents with bipolar disorders. NeuroImage: Clinical, 11, 476–485. https://doi.org/10.1016/j.nicl.2016.03.013
80.
UroševićS.YoungstromE. A.CollinsP.JensenJ. B.LucianaM. (2016). Associations of age with reward delay discounting and response inhibition in adolescents with bipolar disorders. Journal of Affective Disorders, 190, 649–656. https://doi.org/10.1016/j.jad.2015.11.005
81.
Van LeijenhorstL.ZanolieK.Van MeelC. S.WestenbergP. M.RomboutsS. A. R. B.CroneE. A. (2010). What motivates the adolescent? Brain regions mediating reward sensitivity across adolescence. Cerebral Cortex, 20(1), 61–69. https://doi.org/10.1093/cercor/bhp078
82.
Van RheenenT. E.LewandowskiK. E.BauerI. E.KapczinskiF.MiskowiakK.BurdickK. E.Balanzá-MartínezV. (2020). Current understandings of the trajectory and emerging correlates of cognitive impairment in bipolar disorder: An overview of evidence. Bipolar Disorders, 22(1), 13–27. https://doi.org/10.1111/bdi.12821
83.
Van RheenenT. E.MiskowiakK.BurdickK. E. (2021). Recognising the relevance of cognitive dysfunction in the clinical management of bipolar disorder. Bipolar Disorders, 23(4), 414–415. https://doi.org/10.1111/bdi.13063
84.
VriezeE.PizzagalliD. A.DemyttenaereK.HompesT.SienaertP.de BoerP.SchmidtM.ClaesS. (2013). Reduced reward learning predicts outcome in major depressive disorder. Biological Psychiatry, 73(7), 639–645. https://doi.org/10.1016/j.biopsych.2012.10.014
85.
WagnerS.MüllerC.HelmreichI.HussM.TadićA. (2015). A meta-analysis of cognitive functions in children and adolescents with major depressive disorder. European Child & Adolescent Psychiatry, 24(1), 5–19. https://doi.org/10.1007/s00787-014-0559-2
86.
WatsonD.ClarkL. A.WeberK.AssenheimerJ. S. (1995). Testing a tripartite model II: Exploring the symptom structure of anxiety and depression in student, adult, and patient samples. Journal of Abnormal Psychology, 104(1), 15–25. https://doi.org/10.1037/0021-843x.104.1.15
87.
WatsonD.ClarkL. A.WeberK.AssenheimerJ. S.StraussM. E.McCormickR. A. (1995). Testing a tripartite model I: Evaluating the convergent and discriminant validity of anxiety and depression symptom scales. Journal of Abnormal Psychology, 104(1), 3–14. https://doi.org/10.1037/0021-843x.104.1.3
88.
WilcoxR. R.KeselmanH. J. (2003). Modern robust data analysis methods: Measures of central tendency. Psychological Methods, 8(3), 254–274. https://doi.org/10.1037/1082-989X.8.3.254
89.
YaziciE.BursaliogluF. S.AydinN.YaziciA. B. (2013). Menarche, puberty and psychiatric disorders. Gynecological Endocrinology, 29(12), 1055–1058. https://doi.org/10.3109/09513590.2013.829447
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
