Inhibitory control is central to many theories of cognitive and brain development, and impairments in inhibitory control are posited to underlie developmental psychopathology. In this study, we tested the possibility of shared versus unique associations between inhibitory control and three common symptom dimensions in youth psychopathology: attention-deficit/hyperactivity disorder (ADHD), anxiety, and irritability. We quantified inhibitory control using four different experimental tasks to estimate a latent variable in 246 youth (8–18 years old) with varying symptom types and levels. Participants were recruited from the Washington, D.C., metro region. Results of structural equation modeling integrating a bifactor model of psychopathology revealed that inhibitory control predicted a shared or general psychopathology dimension, but not ADHD-specific, anxiety-specific, or irritability-specific dimensions. Inhibitory control also showed a significant, selective association with global efficiency in a frontoparietal control network delineated during resting-state functional magnetic resonance imaging. These results support performance-based inhibitory control linked to resting-state brain function as an important predictor of comorbidity in youth psychopathology.
AchenbachT. M. (2015). Transdiagnostic heterogeneity, hierarchical dimensional models, and societal, cultural, and individual differences in the developmental understanding of psychopathology. European Child & Adolescent Psychiatry, 24(12), 1419–1422. https://doi.org/10.1007/s00787-015-0795-0
2.
AldersonR. M.RapportM. D.KoflerM. J. (2007). Attention-deficit/hyperactivity disorder and behavioral inhibition: A meta-analytic review of the stop-signal paradigm. Journal of Abnormal Child Psychology, 35(5), 745–758. https://doi.org/10.1007/s10802-007-9131-6
3.
Bashford-LargoJ.AloiJ.LukoffJ.JohnsonK.WhiteS. F.DobbertinM.BlairR. J.BlairK. S. (2021). Reduced top-down attentional control in adolescents with generalized anxiety disorder. Brain and Behavior, 11(2), Article e01994. https://doi.org/10.1002/brb3.1994
4.
BirmaherB.KhetarpalS.BrentD.CullyM.BalachL.KaufmanJ.NeerS. M. (1997). The Screen for Child Anxiety Related Emotional Disorders (SCARED): Scale construction and psychometric characteristics. Journal of the American Academy of Child & Adolescent Psychiatry, 36(4), 545–553. https://doi.org/10.1097/00004583-199704000-00018
5.
BlondelV. D.GuillaumeJ.-L.LambiotteR.LefebvreE. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10008. https://doi.org/10.1088/1742-5468/2008/10/P10008
6.
BornovalovaM. A.ChoateA. M.FatimahH.PetersenK. J.WiernikB. M. (2020). Appropriate use of bifactor analysis in psychopathology research: Appreciating benefits and limitations. Biological Psychiatry, 88(1), 18–27. https://doi.org/10.1016/j.biopsych.2020.01.013
7.
BraverT. S.BarchD. M.KeysB. A.CarterC. S.CohenJ. D.KayeJ. A.JanowskyJ. S.TaylorS. F.YesavageJ. A.MumenthalerM. S.JagustW. J.ReedB. R. (2001). Context processing in older adults: Evidence for a theory relating cognitive control to neurobiology in healthy aging. Journal of Experimental Psychology: General, 130(4), 746–763. https://doi.org/10.1037/0096-3445.130.4.746
8.
BuzzellG. A.MoralesS.BowersM. E.Troller-RenfreeS. V.Chronis-TuscanoA.PineD. S.HendersonH. A.FoxN. A. (2021). Inhibitory control and set shifting describe different pathways from behavioral inhibition to socially anxious behavior. Developmental Science, 24(1), Article e13040. https://doi.org/10.1111/desc.13040
9.
CaiW.GriffithsK.KorgaonkarM. S.WilliamsL. M.MenonV. (2021). Inhibition-related modulation of salience and frontoparietal networks predicts cognitive control ability and inattention symptoms in children with ADHD. Molecular Psychiatry, 26(8), 4016–4025. https://doi.org/10.1038/s41380-019-0564-4
10.
CardinaleE. M.KircanskiK.BrooksJ.GoldA. L.TowbinK. E.PineD. S.LeibenluftE.BrotmanM. A. (2019). Parsing neurodevelopmental features of irritability and anxiety: Replication and validation of a latent variable approach. Development and Psychopathology, 31, 917–929. https://doi.org/10.1017/S095457941900035X
11.
CarverC. S.JohnsonS. L.TimpanoK. R. (2017). Toward a functional view of the p factor in psychopathology. Clinical Psychological Science, 5(5), 880–889. https://doi.org/10.1177/2167702617710037
12.
CastellanosF. X.Sonuga-BarkeE. J. S.MilhamM. P.TannockR. (2006). Characterizing cognition in ADHD: Beyond executive dysfunction. Trends in Cognitive Sciences, 10(3), 117–123. https://doi.org/10.1016/j.tics.2006.01.011
13.
ChenY.HuangX.WuM.LiK.HuX.JiangP.ChenL.HeN.DaiJ.WangS.HeM.GuoL.SweeneyJ. A.GongQ. (2019). Disrupted brain functional networks in drug-naïve children with attention deficit hyperactivity disorder assessed using graph theory analysis. Human Brain Mapping, 40(17), 4877–4887. https://doi.org/10.1002/hbm.24743
14.
ColonnaS.EyreO.AghaS. S.ThaparA.Van GoozenS.LangleyK. (2022). Investigating the associations between irritability and hot and cool executive functioning in those with ADHD. BMC Psychiatry, 22(1), Article 166. https://doi.org/10.1186/s12888-022-03818-1
15.
ConnersC. K.PitkanenJ.RzepaS. R. (2011). Conners comprehensive behavior rating scale. In KreutzerJ. S.DeLucaJ.CaplanB. (Eds.), Encyclopedia of clinical neuropsychology (pp. 678–680). Springer.
EssauC. A.De La Torre-LuqueA. (2023). Comorbidity between internalising and externalising disorders among adolescents: Symptom connectivity features and psychosocial outcome. Child Psychiatry & Human Development, 54(2), 493–507. https://doi.org/10.1007/s10578-021-01264-w
18.
EstebanO.BirmanD.SchaerM.KoyejoO. O.PoldrackR. A.GorgolewskiK. J. (2017). MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites. PLOS ONE, 12(9), Article e0184661. https://doi.org/10.1371/journal.pone.0184661
19.
FilippiC. A.SubarA.RaviS.HaasS.Troller-RenfreeS. V.FoxN. A.LeibenluftE.PineD. S. (2022). Developmental changes in the association between cognitive control and anxiety. Child Psychiatry & Human Development, 53(3), 599–609. https://doi.org/10.1007/s10578-021-01150-5
20.
HoffmannM. S.MooreT. M.Kvitko AxelrudL.TottenhamN.ZuoX.-N.RohdeL. A.MilhamM. P.SatterthwaiteT. D.SalumG. A. (2022). Reliability and validity of bifactor models of dimensional psychopathology in youth. Journal of Psychopathology and Clinical Science, 131(4), 407–421. https://doi.org/10.1037/abn0000749
21.
KaufmanJ.BirmaherB.BrentD.RaoU.FlynnC.MoreciP.WilliamsonD.RyanN. (1997). Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL): Initial reliability and validity data. Journal of the American Academy of Child & Adolescent Psychiatry, 36(7), 980–988. https://doi.org/10.1097/00004583-199707000-00021
LiY.GrabellA. S.WakschlagL. S.HuppertT. J.PerlmanS. B. (2017). The neural substrates of cognitive flexibility are related to individual differences in preschool irritability: A fNIRS investigation. Developmental Cognitive Neuroscience, 25, 138–144. https://doi.org/10.1016/j.dcn.2016.07.002
25.
LijffijtM.KenemansJ. L.VerbatenM. N.van EngelandH. (2005). A meta-analytic review of stopping performance in attention-deficit/hyperactivity disorder: Deficient inhibitory motor control?Journal of Abnormal Psychology, 114(2), 216–222. https://doi.org/10.1037/0021-843X.114.2.216
LinkeJ. O.HallerS. P.XuE. P.NguyenL. T.ChueA. E.Botz-ZappC.RevzinaO.PerlsteinS.RossA. J.TsengW.-L.ShawP.BrotmanM. A.PineD. S.GottsS. J.LeibenluftE.KircanskiK. (2023). Persistent frustration-induced reconfigurations of brain networks predict individual differences in irritability. Journal of the American Academy of Child & Adolescent Psychiatry, 62(6), 684–695. https://doi.org/10.1016/j.jaac.2022.11.009
28.
LipszycJ.SchacharR. (2010). Inhibitory control and psychopathology: A meta-analysis of studies using the stop signal task. Journal of the International Neuropsychological Society, 16(6), 1064–1076. https://doi.org/10.1017/S1355617710000895
29.
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
30.
MaL.MazidiM.LiK.LiY.ChenS.KirwanR.ZhouH.YanN.RahmanA.WangW.WangY. (2021). Prevalence of mental health problems among children and adolescents during the COVID-19 pandemic: A systematic review and meta-analysis. Journal of Affective Disorders, 293, 78–89. https://doi.org/10.1016/j.jad.2021.06.021
31.
MarekS.Tervo-ClemmensB.CalabroF. J.MontezD. F.KayB. P.HatoumA. S.DonohueM. R.ForanW.MillerR. L.HendricksonT. J.MaloneS. M.KandalaS.FeczkoE.Miranda-DominguezO.GrahamA. M.EarlE. A.PerroneA. J.CordovaM.DoyleO.. . . DosenbachN. U. F. (2022). Reproducible brain-wide association studies require thousands of individuals. Nature, 603(7902), 654–660. https://doi.org/10.1038/s41586-022-04492-9
32.
MartelM. M.PanP. M.HoffmannM. S.GadelhaA.do RosárioM. C.MariJ. J.ManfroG. G.MiguelE. C.PausT.BressanR. A.RohdeL. A.SalumG. A. (2017). A general psychopathology factor (P factor) in children: Structural model analysis and external validation through familial risk and child global executive function. Journal of Abnormal Psychology, 126(1), 137–148. https://doi.org/10.1037/abn0000205
33.
MartelM. M.RobertsB.GremillionM. L. (2013). Emerging control and disruptive behavior disorders during early childhood. Developmental Neuropsychology, 38(3), 153–166. https://doi.org/10.1080/87565641.2012.758731
34.
MenonV. (2011). Large-scale brain networks and psychopathology: A unifying triple network model. Trends in Cognitive Sciences, 15(10), 483–506. https://doi.org/10.1016/j.tics.2011.08.003
35.
MenonV. (2013). Developmental pathways to functional brain networks: Emerging principles. Trends in Cognitive Sciences, 17(12), 627–640.
36.
MenonV.D’EspositoM. (2022). The role of PFC networks in cognitive control and executive function. Neuropsychopharmacology, 47(1), 90–103. https://doi.org/10.1038/s41386-021-01152-w
37.
MiyakeA.FriedmanN. P. (2012). The nature and organization of individual differences in executive functions: Four general conclusions. Current Directions in Psychological Science, 21(1), 8–14. https://doi.org/10.1177/0963721411429458
38.
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
OldhamS.FornitoA. (2019). The development of brain network hubs. Developmental Cognitive Neuroscience, 36, Article 100607. https://doi.org/10.1016/j.dcn.2018.12.005
41.
PerhamusG. R.OstrovJ. M. (2023). Inhibitory control in early childhood aggression subtypes: Mediation by irritability. Child Psychiatry & Human Development, 54(2), 366–378. https://doi.org/10.1007/s10578-021-01254-y
42.
PruimR. H. R.MennesM.van RooijD.LleraA.BuitelaarJ. K.BeckmannC. F. (2015). ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data. NeuroImage, 112, 267–277. https://doi.org/10.1016/j.neuroimage.2015.02.064
43.
ReinebergA. E.Andrews-HannaJ. R.DepueB. E.FriedmanN. P.BanichM. T. (2015). Resting-state networks predict individual differences in common and specific aspects of executive function. NeuroImage, 104, 69–78. https://doi.org/10.1016/j.neuroimage.2014.09.045
44.
ReiseS. P.MansolfM.HavilandM. G. (2022). Bifactor measurement models. In HoyleR. (Ed.), Handbook of structural equation modeling (pp. 329–348). Guilford Press.
SchaeferA.KongR.GordonE. M.LaumannT. O.ZuoX.-N.HolmesA. J.EickhoffS. B.YeoB. T. T. (2018). Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI. Cerebral Cortex, 28(9), 3095–3114. https://doi.org/10.1093/cercor/bhx179
48.
SnyderH. R.HankinB. L. (2017). All models are wrong, but the p factor model is useful: Reply to Widiger and Oltmanns (2017) and Bonifay, Lane, and Reise (2017). Clinical Psychological Science, 5(1), 187–189. https://doi.org/10.1177/2167702616659389
49.
StringarisA.GoodmanR.FerdinandoS.RazdanV.MuhrerE.LeibenluftE.BrotmanM. A. (2012). The affective reactivity index: A concise irritability scale for clinical and research settings: The affective reactivity index. Journal of Child Psychology and Psychiatry, 53(11), 1109–1117. https://doi.org/10.1111/j.1469-7610.2012.02561.x
50.
Troller-RenfreeS. V.BuzzellG. A.PineD. S.HendersonH. A.FoxN. A. (2019). Consequences of not planning ahead: Reduced proactive control moderates longitudinal relations between behavioral inhibition and anxiety. Journal of the American Academy of Child & Adolescent Psychiatry, 58(8), 768–775. https://doi.org/10.1016/j.jaac.2018.06.040
51.
VenablesN. C.FoellJ.YanceyJ. R.KaneM. J.EngleR. W.PatrickC. J. (2018). Quantifying inhibitory control as externalizing proneness: A cross-domain model. Clinical Psychological Science, 6, 561–580.
52.
WattsA. L.PooreH. E.WaldmanI. D. (2019). Riskier tests of the validity of the bifactor model of psychopathology. Clinical Psychological Science, 7(6), 1285–1303. https://doi.org/10.1177/2167702619855035
53.
ZeeuwP. D.Aarnoudse-MoensC.BijlhoutJ.KönigC.UiterweerA. P.PapanikolauA.HoogenraadC.ImandtL.BeenD. D.SergeantJ. A.OosterlaanJ. (2008). Inhibitory performance, response speed, intraindividual variability, and response accuracy in ADHD. Journal of the American Academy of Child & Adolescent Psychiatry, 47(7), 808–816. https://doi.org/10.1097/CHI.0b013e318172eee9
54.
ZhangR.GengX.LeeT. M. C. (2017). Large-scale functional neural network correlates of response inhibition: An fMRI meta-analysis. Brain Structure and Function, 222(9), 3973–3990. https://doi.org/10.1007/s00429-017-1443-x
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