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Mental Health Problems are Associated with Low-Frequency Fluctuations in Reaction Time in A Large General Population Sample. The TRAILS Study

Published online by Cambridge University Press:  15 April 2020

J.A. Bastiaansen ,
A.M. van Roon ,
J.K. Buitelaar  and
A.J. Oldehinkel
J.A. Bastiaansen*
Affiliation:
Interdisciplinary Center Psychopathology and Emotion regulation, Department of Psychiatry, University Medical Center Groningen, CC72, PO Box 30.001, 9700 RBGroningen, The Netherlands
A.M. van Roon
Affiliation:
Department of Internal Medicine, University Medical Center Groningen, Hanzeplein 1, 9713 GZGroningen, The Netherlands
J.K. Buitelaar
Affiliation:
Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Nijmegen Medical Center, PO Box 9101, 6500 HBNijmegen, The Netherlands
A.J. Oldehinkel
Affiliation:
Interdisciplinary Center Psychopathology and Emotion regulation, Department of Psychiatry, University Medical Center Groningen, CC72, PO Box 30.001, 9700 RBGroningen, The Netherlands
*
*Corresponding author. Tel.: +31 5 03 61 11 69; fax: +31 5 03 61 97 22. E-mail address:j.bastiaansen@umcg.nl (J.A. Bastiaansen).
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Abstract

Background:

Increased intra-subject reaction time variability (RT-ISV) as coarsely measured by the standard deviation (RT-SD) has been associated with many forms of psychopathology. Low-frequency RT fluctuations, which have been associated with intrinsic brain rhythms occurring approximately every 15–40 s, have been shown to add unique information for ADHD. In this study, we investigated whether these fluctuations also relate to attentional problems in the general population, and contribute to the two major domains of psychopathology: externalizing and internalizing problems.

Methods:

RT was monitored throughout a self-paced sustained attention task (duration: 9.1 ± 1.2 min) in a Dutch population cohort of young adults (n = 1455, mean age: 19.0 ± 0.6 years, 55.1% girls). To characterize temporal fluctuations in RT, we performed direct Fourier Transform on externally validated frequency bands based on frequency ranges of neuronal oscillations: Slow-5 (0.010–0.027 Hz), Slow-4 (0.027–0.073 Hz), and three additional higher frequency bands. Relative magnitude of Slow-4 fluctuations was the primary predictor in regression models for attentional, internalizing and externalizing problems (measured by the Adult Self-Report questionnaire). Additionally, stepwise regression models were created to investigate (a) whether Slow-4 significantly improved the prediction of problem behaviors beyond the RT-SD and (b) whether the other frequency bands provided important additional information.

Results:

The magnitude of Slow-4 fluctuations significantly predicted attentional and externalizing problems and even improved model fit after modeling RT-SD first (R2 change = 0.6%, P < .01). Subsequently, adding Slow-5 explained additional variance for externalizing problems (R2 change = 0.4%, P < .05). For internalizing problems, only RT-SD made a significant contribution to the regression model (R2 = 0.5%, P < .01), that is, none of the frequency bands provided additional information.

Conclusions:

Low-frequency RT fluctuations have added predictive value for attentional and externalizing, but not internalizing problems beyond global differences in variability. This study extends previous findings in clinical samples of children with ADHD to adolescents from the general population and demonstrates that deconstructing RT-ISV into temporal components can provide more distinctive information for different domains of psychopathology.

Keywords

AttentionIntra-individual variabilityFourier transformDefault modePsychopathology
Type
Original article
Information
European Psychiatry , Volume 30 , Issue 2 , February 2015 , pp. 347 - 353
Copyright
Copyright © Elsevier Masson SAS 2014

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Footnotes

1

Tel.: +31 5 03 61 20 97; fax: +31 5 03 61 33 12.

2

Tel.: +31 2 43 61 06 55.

3

Tel.: +31 5 03 61 45 50; fax: +31 5 03 61 97 22.

References

Achenbach, T.M., Rescorla, L.Manual for the ASEBA school-age forms & profiles: an integrated system of multi-informant assessment. Burlington, Vermont: University of Vermont, Research Center for Children, Youth and Families; 2001.Google Scholar
Baumeister, A.A.Intelligence and the “personal equation”. Intelligence 1998;26 :255–265.CrossRefGoogle Scholar
Bellgrove, M.A., Hester, R., Garavan, H.The functional neuroanatomical correlates of response variability: evidence from a response inhibition task. Neuropsychologia 2004;42 :1910–1916.CrossRefGoogle ScholarPubMed
Brotman, M.A., Rooney, M.H., Skup, M., Pine, D.S., Leibenluft, E.Increased intrasubject variability in response time in youths with bipolar disorder and at-risk family members. J Am Acad Child Adolesc Psychiatry 2009;48 :628–635.CrossRefGoogle ScholarPubMed
Brunnekreef, A., De Sonneville, L.M.J., Althaus, M., Minderaa, R.B., Oldehinkel, A.J., Verhulst, F.C., et al.Information processing profiles of internalizing and externalizing behavior problems: evidence from a population-based sample of preadolescents. J Child Psychol Psychiatry 2007;48 :185–193.CrossRefGoogle Scholar
Buzsáki, G., Draguhn, A.Neuronal oscillations in cortical networks. Science 2004;304 :1926–1929.CrossRefGoogle ScholarPubMed
Castellanos, F.X., Tannock, R.Neuroscience of attention-deficit/hyperactivity disorder: the search for endophenotypes. Nat Rev Neurosci 2002;3 :617–628.CrossRefGoogle ScholarPubMed
Castellanos, F.X., Sonuga-Barke, E.J.S., Scheres, A., Di Martino, A., Hyde, C., Walters, J.R.Varieties of attention-deficit/hyperactivity disorder-related intra-individual variability. Biol Psychiatry 2005;57 :1416–1423.CrossRefGoogle ScholarPubMed
Castellanos, F.X., Sonuga-Barke, E.J.S., Milham, M.P., Tannock, R.Characterizing cognition in ADHD: beyond executive dysfunction. Trends Cogn Sci 2006;10 :117–123.CrossRefGoogle ScholarPubMed
Castellanos, F.X., Margulies, D.S., Kelly, C., Uddin, L.Q., Ghaffari, M., Kirsch, A., et al.Cingulate-precuneus interactions: a new locus of dysfunction in adult attention-deficit/hyperactivity disorder. Biol Psychiatry 2008;63 :332–337.CrossRefGoogle ScholarPubMed
Cordes, D., Haughton, V.M., Arfanakis, K., Carew, J.D., Turski, P.A., Moritz, C.H., et al.Frequencies contributing to functional connectivity in the cerebral cortex in “resting-state” data. AJNR Am J Neuroradiol 2001;22 :1326–1333.Google ScholarPubMed
Dalwani, M.S., Tregellas, J.R., Andrews-Hanna, J.R., Mikulich-Gilbertson, S.K., Raymond, K.M., Banich, M.T., et al.Default mode network activity in male adolescents with conduct and substance use disorder. Drug Alcohol Depend 2014;134 :242–250.CrossRefGoogle ScholarPubMed
De Sonneville, L.M.J.Amsterdam Neuropsychological Tasks: a computer-aided assessment program. In: den Brinker, B.P.L.M., Beek, P.J., Brand, A.N., Maarse, S.J., Mulder, L.J.M., editors. Cognitive ergonomics, clinical assessment and computer-assisted learning: Computers in Psychology Lisse, The Netherlands: Swets & Zeitlinger; 1999. p. 187–203.Google Scholar
De Winter, A.F., Oldehinkel, A.J., Veenstra, R., Brunnekreef, J.A., Verhulst, F.C., Ormel, J.Evaluation of non-response bias in mental health determinants and outcomes in a large sample of pre-adolescents. Eur J Epidemiol 2005;20 :173–181.CrossRefGoogle Scholar
Depp, C.A., Savla, G.N., de Dios, L.A.V., Mausbach, B.T., Palmer, B.W.Affective symptoms and intra-individual variability in the short-term course of cognitive functioning in bipolar disorder. Psychol Med 2011;42 :1409–1416.CrossRefGoogle ScholarPubMed
Di Martino, A., Ghaffari, M., Curchack, J., Reiss, P., Hyde, C., Vannucci, M., et al.Decomposing intra-subject variability in children with attention-deficit/hyperactivity disorder. Biol Psychiatry 2008;64 :607–614.CrossRefGoogle ScholarPubMed
Dietrich, A., Riese, H., van Roon, A.M., van Engelen, K., Ormel, J., Neeleman, J., et al.Spontaneous baroreflex sensitivity in (pre)adolescents. J Hypertens 2006;24 :345–352.CrossRefGoogle ScholarPubMed
Eichele, T., Debener, S., Calhoun, V.D., Specht, K., Engel, A.K., Hugdahl, K., et al.Prediction of human errors by maladaptive changes in event-related brain networks. Proc Natl Acad Sci U S A 2008;105 :6173–6178.CrossRefGoogle ScholarPubMed
Eisenberg, N., Valiente, C., Spinrad, T.L., Liew, J., Zhou, Q., Losoya, S.H., et al.Longitudinal relations of children's effortful control, impulsivity, and negative emotionality to their externalizing, internalizing, and co-occurring behavior problems. Dev Psychol 2009;45 :988–1008.CrossRefGoogle ScholarPubMed
Fassbender, C., Zhang, H., Buzy, W.M., Cortes, C.R., Mizuiri, D., Beckett, L., et al.A lack of default network suppression is linked to increased distractibility in ADHD. Brain Res 2009;1273 :114–128.CrossRefGoogle ScholarPubMed
Fox, M.D., Raichle, M.E.Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 2007;8 :700–711.CrossRefGoogle ScholarPubMed
Fox, M.D., Snyder, A.Z., Vincent, J.L., Corbetta, M., Van Essen, D.C., Raichle, M.E.The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A 2005;102 :9673–9678.CrossRefGoogle ScholarPubMed
Fox, M.D., Snyder, A.Z., Vincent, J.L., Raichle, M.E.Intrinsic fluctuations within cortical systems account for intertrial variability in human behavior. Neuron 2007;56 :171–184.CrossRefGoogle ScholarPubMed
Geurts, H.M., Grasman, R.P.P.P., Verté, S., Oosterlaan, J., Roeyers, H., van Kammen, S.M., et al.Intra-individual variability in ADHD, autism spectrum disorders and Tourette's syndrome. Neuropsychologia 2008;46 :3030–3041.CrossRefGoogle ScholarPubMed
Han, Y., Wang, J., Zhao, Z., Min, B., Lu, J., Li, K., et al.Frequency-dependent changes in the amplitude of low-frequency fluctuations in amnestic mild cognitive impairment: A resting-state fMRI study. NeuroImage 2011;55 :287–295.CrossRefGoogle ScholarPubMed
Hoekzema, E., Carmona, S., Ramos-Quiroga, J.A., Richarte Fernández, V., Bosch, R., Soliva, J.C., et al.An independent components and functional connectivity analysis of resting state fMRI data points to neural network dysregulation in adult ADHD. Hum Brain Mapp 2013;35 :1261–1272.CrossRefGoogle ScholarPubMed
Huisman, M.Imputation of missing item responses: some simple techniques. Qual Quant 2000;34 :331–351.CrossRefGoogle Scholar
Huisman, M., Oldehinkel, A.J., de Winter, A., Minderaa, R.B., de Bildt, A., Huizink, A.C., et al.Cohort profile: the Dutch “TRacking Adolescents” Individual Lives’ Survey’; TRAILS. Int J Epidemiol 2008;37 :1227–1235.CrossRefGoogle Scholar
Hutchison, W.D., Dostrovsky, J.O., Walters, J.R., Courtemanche, R., Boraud, T., Goldberg, J., et al.Neuronal oscillations in the basal ganglia and movement disorders: evidence from whole animal and human recordings. J Neurosci 2004;24 :9240–9243.CrossRefGoogle ScholarPubMed
Jensen, A.R.The importance of intraindividual variation in reaction time. Pers Individ Dif 1992;13 :869–881.CrossRefGoogle Scholar
Johnson, K.A., Kelly, S.P., Bellgrove, M.A., Barry, E., Cox, M., Gill, M., et al.Response variability in attention deficit hyperactivity disorder: evidence for neuropsychological heterogeneity. Neuropsychologia 2007;45 :630–638.CrossRefGoogle ScholarPubMed
Johnson, K.A., Robertson, I.H., Kelly, S.P., Silk, T.J., Barry, E., Dáibhis, A., et al.Dissociation in performance of children with ADHD and high-functioning autism on a task of sustained attention. Neuropsychologia 2007;45 :2234–2245.CrossRefGoogle ScholarPubMed
Kaiser, S., Roth, A., Rentrop, M., Friederich, H.-C., Bender, S., Weisbrod, M.Intra-individual reaction time variability in schizophrenia, depression and borderline personality disorder. Brain Cogn 2008;66 :73–82.CrossRefGoogle ScholarPubMed
Karalunas, S.L., Huang-Pollock, C.L., Nigg, J.T.Is reaction time variability in ADHD mainly at low frequencies?. J Child Psychol Psychiatry 2012;54 :536–544.CrossRefGoogle ScholarPubMed
Krueger, R.F., South, S.C.Externalizing disorders: cluster 5 of the proposed meta-structure for DSM-V and ICD-11. Psychol Med 2009;39 :2061–2070.CrossRefGoogle ScholarPubMed
Liddle, E.B., Hollis, C., Batty, M.J., Groom, M.J., Totman, J.J., Liotti, M., et al.Task-related default mode network modulation and inhibitory control in ADHD: effects of motivation and methylphenidate. J Child Psychol Psychiatry 2011;52 :761–771.CrossRefGoogle ScholarPubMed
MacDonald, S.W.S., Nyberg, L., Bäckman, L.Intra-individual variability in behavior: links to brain structure, neurotransmission and neuronal activity. Trends Neurosci 2006;29 :474–480.CrossRefGoogle ScholarPubMed
Marchetti, I., Koster, E.H.W., Sonuga-Barke, E.J., Raedt, R.D.The default mode network and recurrent depression: a neurobiological model of cognitive risk factors. Neuropsychol Rev 2012;22 :229–251.CrossRefGoogle ScholarPubMed
Mason, M.F., Norton, M.I., Van Horn, J.D., Wegner, D.M., Grafton, S.T., Macrae, C.N.Wandering minds: the default network and stimulus-independent thought. Science 2007;315 :393–395.CrossRefGoogle ScholarPubMed
Nederhof, E., Jörg, F., Raven, D., Veenstra, R., Verhulst, F.C., Ormel, J., et al.Benefits of extensive recruitment effort persist during follow-ups and are consistent across age group and survey method. The TRAILS study. BMC Med Res Methodol 2012;12 :93.CrossRefGoogle ScholarPubMed
Oldehinkel, A.J., Hartman, C.A., De Winter, A.F., Veenstra, R., Ormel, J.Temperament profiles associated with internalizing and externalizing problems in preadolescence. Dev Psychopathol 2004;16 :421–440.CrossRefGoogle ScholarPubMed
Ormel, J., Oldehinkel, A.J., Sijtsema, J., van Oort, F., Raven, D., Veenstra, R., et al.The TRacking Adolescents’ Individual Lives Survey (TRAILS): design, current status, and selected findings. J Am Acad Child Adolesc Psychiatry 2012;51 :1020–1036.CrossRefGoogle ScholarPubMed
Penttonen, M., Buzsáki, G.Natural logarithmic relationship between brain oscillators. Thalamus Relat Syst 2003;2 :145–152.CrossRefGoogle Scholar
Peterson, B.S., Potenza, M.N., Wang, Z., Zhu, H., Martin, A., Marsh, R., et al.An FMRI study of the effects of psychostimulants on default-mode processing during Stroop task performance in youths with ADHD. Am J Psychiatry 2009;166 :1286–1294.CrossRefGoogle ScholarPubMed
Raichle, M.E., MacLeod, A.M., Snyder, A.Z., Powers, W.J., Gusnard, D.A., Shulman, G.L.A default mode of brain function. Proc Natl Acad Sci U S A 2001;98 :676–682.CrossRefGoogle ScholarPubMed
Sonuga-Barke, E.J.S., Castellanos, F.X.Spontaneous attentional fluctuations in impaired states and pathological conditions: a neurobiological hypothesis. Neurosci Biobehav Rev 2007;31 :977–986.CrossRefGoogle ScholarPubMed
Stuss, D.T., Murphy, K.J., Binns, M.A., Alexander, M.P.Staying on the job: the frontal lobes control individual performance variability. Brain 2003;126 :2363–2380.CrossRefGoogle ScholarPubMed
Tang, Y., Jiang, W., Liao, J., Wang, W., Luo, A.Identifying individuals with antisocial personality disorder using resting-state FMRI. PLoS One 2013;8 :e60652.CrossRefGoogle ScholarPubMed
Van Deurzen, P., Buitelaar, J., Agnes Brunnekreef, J., Ormel, J., Minderaa, R., Hartman, C., et al.Response time variability and response inhibition predict affective problems in adolescent girls, not in boys: the TRAILS study. Eur Child Adolesc Psychiatry 2012;21 :277–287.CrossRefGoogle Scholar
Weissman, D.H., Roberts, K.C., Visscher, K.M., Woldorff, M.G.The neural bases of momentary lapses in attention. Nat Neurosci 2006;9 :971–978.CrossRefGoogle ScholarPubMed
Yordanova, J., Albrecht, B., Uebel, H., Kirov, R., Banaschewski, T., Rothenberger, A., et al.Independent oscillatory patterns determine performance fluctuations in children with attention deficit/hyperactivity disorder. Brain 2011;134 :1740–1750.CrossRefGoogle ScholarPubMed
Zahn, T.P., Kruesi, M.J., Rapoport, J.L.Reaction time indices of attention deficits in boys with disruptive behavior disorders. J Abnorm Child Psychol 1991;19 :233–252.CrossRefGoogle ScholarPubMed
Zuo, X.-N., Di Martino, A., Kelly, C., Shehzad, Z.E., Gee, D.G., Klein, D.F., et al.The oscillating brain: complex and reliable. Neuroimage 2010;49 :1432–1445.CrossRefGoogle ScholarPubMed
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