Restricted accessResearch articleFirst published online 2019-11
Integration and Segregation of the Brain Relate to Stability of Performance in Children and Adolescents with Varied Levels of Inattention and Impulsivity
It is common to find that individuals with attention-deficit/hyperactivity disorder (ADHD) produce more variable responses when performing cognitive tasks. The neural mechanism associated with heightened response time variability (RTV) is not well understood in ADHD nor in typically developing individuals. One potential mechanism that might be associated with increased RTV is functional connectivity of the brain, and specifically inefficient connections. This study examined the relationships among functional connectivity of the brain, RTV, and levels of ADHD symptoms, using a cross-sectional developmental design. Twenty children aged 9–12 years and 49 adolescents aged 15–18 years completed the Sustained Attention to Response Task with flanker interference while electroencephalography (EEG) was recorded. The Conners 3 questionnaire was used to measure the participants' levels of ADHD symptoms. Parameters reflecting different aspects of RTV were computed using ex-Gaussian and fast Fourier transform techniques. Functional connectivity between 64 electrodes was computed for the task period, and global efficiency reflecting functional integration and modularity reflecting strength of functional segregation were computed. Greater global efficiency in the theta band was associated with decreased RTV. Increased integration during the task may help to combine information more efficiently and produce stable responses. When congruent flankers were present, children with greater modularity in the beta band showed greater tau, which is thought to reflect attentional lapses. This association was not observed when incongruent flankers were present. Brains with increased strength of segregated activity might be more prone to attentional lapses, especially during simpler tasks.
Get full access to this article
View all access options for this article.
References
1.
Abundis-GutierrezA, ChecaP, CastellanosC, Rosario RuedaM. 2014. Electrophysiological correlates of attention networks in childhood and early adulthood. Neuropsychologia, 57:78–92.
2.
AdamoN, Di MartinoA, EsuL, PetkovaE, JohnsonK, KellyS, et al.2014. Increased response-time variability across different cognitive tasks in children with ADHD. J Atten Disord, 18:434–446.
3.
AlbaughMD, OrrC, ChaaraniB, AlthoffRR, AllgaierN, D'AlbertoN, et al.2017. Inattention and reaction time variability are linked to ventromedial prefrontal volume in adolescents. Biol Psychiatry, 82:660–668.
4.
AlbrechtB, BrandeisD, UebelH, ValkoL, HeinrichH, DrechslerR, et al.2013. Familiality of neural preparation and response control in childhood attention deficit-hyperactivity disorder. Psychol Med, 43:1997–2011.
5.
ArnsM, ConnersCK, KraemerHC. 2013. A Decade of EEG theta/beta ratio research in ADHD: a meta-analysis. J Atten Disord, 17:374–383.
6.
BellgroveMA, HesterR, GaravanH. 2004. The functional neuroanatomical correlates of response variability: evidence from a response inhibition task. Neuropsychologia, 42:1910–1916.
7.
BenjaminiY, HochbergY. 1995. Controlling the false discovery rate—a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol, 57:289–300.
8.
BerthouzeL, JamesLM, FarmerSF. 2010. Human EEG shows long-range temporal correlations of oscillation amplitude in theta, alpha and beta bands across a wide age range. Clin Neurophysiol, 121:1187–1197.
9.
BolaM, SabelBA. 2015. Dynamic reorganization of brain functional networks during cognition. Neuroimage, 114:398–413.
10.
BreckelTP, ThielCM, BullmoreET, ZaleskyA, PatelAX, GiessingC. 2013. Long-term effects of attentional performance on functional brain network topology. PLoS One, 8:e74125.
11.
BroydSJ, HelpsSK, Sonuga-BarkeEJ. 2011. Attention-induced deactivations in very low frequency EEG oscillations: differential localisation according to ADHD symptom status. PLoS One, 6:e17325.
12.
BullmoreE, SpornsO. 2012. The economy of brain network organization. Nat Rev Neurosci, 13:336–349.
13.
CalabriaM, HernandezM, MartinCD, CostaA. 2011. When the tail counts: the advantage of bilingualism through the ex-gaussian distribution analysis. Front Psychol, 2:250.
14.
CaoM, ShuN, CaoQ, WangY, HeY. 2014. Imaging functional and structural brain connectomics in attention-deficit/hyperactivity disorder. Mol Neurobiol, 50:1111–1123.
15.
CastellanosFX, Sonuga-BarkeEJ, ScheresA, Di MartinoA, HydeC, WaltersJR. 2005. Varieties of attention-deficit/hyperactivity disorder-related intra-individual variability. Biol Psychiatry, 57:1416–1423.
16.
CohenJR, D'EspositoM. 2016. The segregation and integration of distinct brain networks and their relationship to cognition. J Neurosci, 36:12083–12094.
17.
CohenMX. 2014. Analyzing Neural Time Series Data: Theory and Practice. Cambridge, MA: The MIT Press.
18.
ConnersCK. 2008. Conners, 3rd ed. North Tonawanda, NY: Multi-Health Systems.
19.
CruzatJ, DecoG, Tauste CampoA, PrincipeA, CalabriaM, CostaA, et al.2018. The dynamics of human cognition: Increasing global integration coupled with decreasing segregation found using iEEG. NeuroImage, 172:492–505.
20.
Di MartinoA, GhaffariM, CurchackJ, ReissP, HydeC, VannucciM, et al.2008. Decomposing intra-subject variability in children with attention-deficit/hyperactivity disorder. Biol Psychiatry, 64:607–614.
21.
EpsteinJN, LangbergJM, RosenPJ, GrahamA, NaradME, AntoniniTN, et al.2011. Evidence for higher reaction time variability for children with ADHD on a range of cognitive tasks including reward and event rate manipulations. Neuropsychology, 25:427–441.
22.
EriksenBA, EriksenCW. 1974. Effects of noise letters upon the identification of a target letter in a nonsearch task. Percept Psychophys, 16:143–149.
23.
ForsterS, RobertsonDJ, JenningsA, AshersonP, LavieN. 2014. Plugging the attention deficit: perceptual load counters increased distraction in ADHD. Neuropsychology, 28:91–97.
24.
FoxMD, SnyderAZ, VincentJL, RaichleME. 2007. Intrinsic fluctuations within cortical systems account for intertrial variability in human behavior. Neuron, 56:171–184.
25.
FrazierTW, YoungstromEA, NaugleRI. 2007. The latent structure of attention-deficit/hyperactivity disorder in a clinic-referred sample. Neuropsychology, 21:45–64.
26.
FriedmanNP, MiyakeA. 2004. The relations among inhibition and interference control functions: a latent-variable analysis. J Exp Psychol Gen, 133:101–135.
27.
Friedman-HillSR, WagmanMR, GexSE, PineDS, LeibenluftE, UngerleiderLG. 2010. What does distractibility in ADHD reveal about mechanisms for top-down attentional control?. Cognition, 115:93–103.
28.
GelmanA, HillJ. 2007. Data Analysis Using Regression and Multilevel Hierarchical Models. New York, NY: Cambridge University Press.
29.
GlickmanME, RaoSR, SchultzMR. 2014. False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies. J Clin Epidemiol, 67:850–857.
30.
Gomez-GuerreroL, MartinCD, MairenaMA, Di MartinoA, WangJ, MendelsohnAL, et al.2011. Response-time variability is related to parent ratings of inattention, hyperactivity, and executive function. J Atten Disord, 15:572–582.
31.
HerveyAS, EpsteinJN, CurryJF, TonevS, Eugene ArnoldL, Keith ConnersC, et al.2006. Reaction time distribution analysis of neuropsychological performance in an ADHD sample. Child Neuropsychol, 12:125–140.
32.
HoganM, KieferM, KubeschS, CollinsP, KilmartinL, BrosnanM. 2013. The interactive effects of physical fitness and acute aerobic exercise on electrophysiological coherence and cognitive performance in adolescents. Exp Brain Res, 229:85–96.
33.
IannacconeR, HauserTU, BallJ, BrandeisD, WalitzaS, BremS. 2015. Classifying adolescent attention-deficit/hyperactivity disorder (ADHD) based on functional and structural imaging. Eur Child Adolesc Psychiatry, 24:1279–1289.
34.
JohnsonKA, BarryE, BellgroveMA, CoxM, KellySP, DaibhisA, et al.2008. Dissociation in response to methylphenidate on response variability in a group of medication naive children with ADHD. Neuropsychologia, 46:1532–1541.
KleinerM, BrainardD, PelliD. 2007. What's new in Psychtoolbox-3?. Perception, 36:14–14.
42.
KnyazevGG, VolfNV, BelousovaLV. 2015. Age-related differences in electroencephalogram connectivity and network topology. Neurobiol Aging, 36:1849–1859.
43.
KoflerMJ, RapportMD, SarverDE, RaikerJS, OrbanSA, FriedmanLM, KolomeyerEG. 2013. Reaction time variability in ADHD: a meta-analytic review of 319 studies. Clin Psychol Rev, 33:795–811.
44.
KonradK, NeufangS, HanischC, FinkGR, Herpertz-DahlmannB. 2006. Dysfunctional attentional networks in children with attention deficit/hyperactivity disorder: evidence from an event-related functional magnetic resonance imaging study. Biol Psychiatry, 59:643–651.
45.
LacoutureY, CousineauD. 2008. How to use MATLAB to fit the ex-Gaussian and other probability functions to a distribution of response times. Tutor Quant Methods Psychol, 4:35–45.
46.
LamersMJ, RoelofsA. 2011. Attentional control adjustments in Eriksen and Stroop task performance can be independent of response conflict. Q J Exp Psychol (Hove), 64:1056–1081.
47.
LenthRV. 2016. Least-squares means: the R package lsmeans. J Stat Softw, 69:1–33.
48.
Leth-SteensenC, ElbazZK, DouglasVI. 2000. Mean response times, variability, and skew in the responding of ADHD children: a response time distributional approach. Acta Psychol (Amst), 104:167–190.
49.
LiSC, HammererD, MullerV, HommelB, LindenbergerU. 2009. Lifespan development of stimulus-response conflict cost: similarities and differences between maturation and senescence. Psychol Res, 73:777–785.
50.
LinP, SunJ, YuG, WuY, YangY, LiangM, LiuX. 2014. Global and local brain network reorganization in attention-deficit/hyperactivity disorder. Brain Imaging Behav, 8:558–569.
51.
LiuT, ChenY, LinP, WangJ. 2015. Small-world brain functional networks in children with attention-deficit/hyperactivity disorder revealed by EEG synchrony. Clin EEG Neurosci, 46:183–191.
52.
LuceRD. 1986. Response Times: Their Role in Inferring Elementary Mental Organization. New York: Oxford University Press, Inc.
53.
MacDonaldSW, LiSC, BäckmanL. 2009. Neural underpinnings of within-person variability in cognitive functioning. Psychol Aging, 24:792.
54.
MairenaMA, Di MartinoA, Dominguez-MartinC, Gomez-GuerreroL, GioiaG, PetkovaE, CastellanosFX. 2012. Low frequency oscillations of response time explain parent ratings of inattention and hyperactivity/impulsivity. Eur Child Adolesc Psychiatry, 21:101–109.
55.
MarcanoJLL, BellMA, BeexAA. Classification of ADHD and non-ADHD using theta/beta power ratio features. In 2017 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI), Orlando, FL, 2017, pp. 345–348.
56.
MatzkeD, WagenmakersEJ. 2009. Psychological interpretation of the ex-Gaussian and shifted Wald parameters: a diffusion model analysis. Psychon Bull Rev, 16:798–817.
57.
McIntoshAR, KovacevicN, ItierRJ. 2008. Increased brain signal variability accompanies lower behavioral variability in development. PLoS Comput Biol, 4:e1000106.
58.
MerktJ, SingmannH, BodenburgS, Goossens-MerktH, KappesA, WendtM, GawrilowC. 2013. Flanker performance in female college students with ADHD: a diffusion model analysis. Atten Defic Hyperact Disord, 5:321–341.
59.
MizuharaH, WangLQ, KobayashiK, YamaguchiY. 2004. A long-range cortical network emerging with theta oscillation in a mental task. Neuroreport, 15:1233–1238.
60.
MullaneJC, CorkumPV, KleinRM, McLaughlinE. 2009. Interference control in children with and without ADHD: a systematic review of Flanker and Simon task performance. Child Neuropsychol, 15:321–342.
61.
MullaneJC, CorkumPV, KleinRM, McLaughlinEN, LawrenceMA. 2011. Alerting, orienting, and executive attention in children with ADHD. J Attent Disord, 15:310–320.
62.
NigburR, CohenMX, RidderinkhofKR, SturmerB. 2012. Theta dynamics reveal domain-specific control over stimulus and response conflict. J Cogn Neurosci, 24:1264–1274.
63.
O'ConnellRG, DockreePM, BellgroveMA, TurinA, WardS, FoxeJJ, RobertsonIH. 2009. Two types of action error: electrophysiological evidence for separable inhibitory and sustained attention neural mechanisms producing error on go/no-go tasks. J Cogn Neurosci, 21:93–104.
64.
OostenveldR, FriesP, MarisE, SchoffelenJM. 2011. FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput Intell Neurosci, 2011: 156869.
65.
RubinovM, SpornsO. 2010. Complex network measures of brain connectivity: uses and interpretations. Neuroimage, 52:1059–1069.
66.
RyanM, JacobsonLA, HagueC, BellowsA, DencklaMB, MahoneEM. 2017. Rapid automatized naming (RAN) in children with ADHD: an ex-Gaussian analysis. Child Neuropsychol, 23:571–587.
67.
SaadJF, KohnMR, ClarkeS, LagopoulosJ, HermensDF. 2018. Is the theta/beta EEG marker for ADHD inherently flawed?. J Atten Disord, 22:815–826.
68.
SamynV, RoeyersH, BijttebierP, WiersemaJR. 2017. Attentional networks in boys with ADHD or autism spectrum disorder and the relationship with effortful control. J Atten Disord, 21:228–239.
SausengP, GriesmayrB, FreunbergerR, KlimeschW. 2010. Control mechanisms in working memory: a possible function of EEG theta oscillations. Neurosci Biobehav Rev, 34:1015–1022.
71.
SausengP, HoppeJ, KlimeschW, GerloffC, HummelFC. 2007. Dissociation of sustained attention from central executive functions: local activity and interregional connectivity in the theta range. Eur J Neurosci, 25:587–593.
72.
ScheresA, OosterlaanJ, SergeantJA. 2001. Response execution and inhibition in children with AD/HD and other disruptive disorders: the role of behavioural activation. J Child Psychol Psychiatry, 42:347–357.
73.
SchulzKP, NewcornJH, FanJ, TangCY, HalperinJM. 2005. Brain activation gradients in ventrolateral prefrontal cortex related to persistence of ADHD in adolescent boys. J Am Acad Child Adolesc Psychiatry, 44:47–54.
74.
SergeantJA. 2005. Modeling attention-deficit/hyperactivity disorder: a critical appraisal of the cognitive-energetic model. Biol Psychiatry, 57:1248–1255.
75.
Sonuga-BarkeEJ, CastellanosFX. 2007. Spontaneous attentional fluctuations in impaired states and pathological conditions: a neurobiological hypothesis. Neurosci Biobehav Rev, 31:977–986.
76.
SpielerDH, BalotaDA, FaustME. 2000. Levels of selective attention revealed through analyses of response time distributions. J Exp Psychol Hum Percept Perform, 26:506–526.
77.
SpornsO. 2013. Networks of the Brain. Cambridge, MA: The MIT Press.
78.
StamCJ, NolteG, DaffertshoferA. 2007. Phase lag index: assessment of functional connectivity from multi channel EEG and MEG with diminished bias from common sources. Hum Brain Mapp, 28:1178–1193.
79.
SuzukiK, OkumuraY, KitaY, OiY, YamashitaY, GotoT, InagakiM. 2017. Excessive hemodynamic activity in the superior frontal cortex during the flanker task in children with attention deficit hyperactivity disorder. Neuroreport, 28:828–832.
80.
TegelbeckersJ, ScharesL, LedererA, BonathB, FlechtnerHH, KrauelK. 2015. Task-irrelevant novel sounds improve attentional performance in children with and without ADHD. Front Psychol, 6:1970.
81.
TothB, BohaR, PosfaiM, GaalZA, KonyaA, StamCJ, MolnarM. 2012. EEG synchronization characteristics of functional connectivity and complex network properties of memory maintenance in the delta and theta frequency bands. Int J Psychophysiol, 83:399–402.
82.
VaidyaCJ, BungeSA, DudukovicNM, ZaleckiCA, ElliottGR, GabrieliJD. 2005. Altered neural substrates of cognitive control in childhood ADHD: evidence from functional magnetic resonance imaging. Am J Psychiatry, 162:1605–1613.
83.
ValenciaM, MartinerieJ, DupontS, ChavezM. 2008. Dynamic small-world behavior in functional brain networks unveiled by an event-related networks approach. Phys Rev E Stat Nonlin Soft Matter Phys, 77(Pt 1):050905.
84.
van MourikR, OosterlaanJ, HeslenfeldDJ, KonigCE, SergeantJA. 2007. When distraction is not distracting: a behavioral and ERP study on distraction in ADHD. Clin Neurophysiol, 118:1855–1865.
85.
van MourikR, PapanikolauA, van Gellicum-BijlhoutJ, van OostenbruggenJ, VeugelersD, Post-UiterweerA, et al.2009. Interference control in children with attention deficit/hyperactivity disorder. J Abnorm Child Psychol, 37:293–303.
86.
VourkasM, MicheloyannisS, SimosPG, RezaieR, FletcherJM, CirinoPT, PapanicolaouAC. 2011. Dynamic task-specific brain network connectivity in children with severe reading difficulties. Neurosci Lett, 488:123–128.
87.
WangL, ZhuC, HeY, ZangY, CaoQ, ZhangH, et al.2009. Altered small-world brain functional networks in children with attention-deficit/hyperactivity disorder. Hum Brain Mapp, 30:638–649.
88.
WangR, LinP, WuY. 2015. Exploring dynamic temporal-topological structure of brain network within ADHD. In: LiljenströmH. (ed.) Advances in Cognitive Neurodynamics (IV). Dordrecht: Springer; pp. 93–98.
89.
WaszakF, LiSC, HommelB. 2010. The development of attentional networks: cross-sectional findings from a life span sample. Dev Psychol, 46:337–349.
90.
WechslerD. 2011. Wechsler Abbreviated Scale of Intelligence—Second Edition (WASI-II). San Antonio, TX: Pearson.
91.
Wild-WallN, OadesRD, Schmidt-WesselsM, ChristiansenH, FalkensteinM. 2009. Neural activity associated with executive functions in adolescents with attention-deficit/hyperactivity disorder (ADHD). Int J Psychophysiol, 74:19–27.
92.
WolfersT, OnninkAMH, ZwiersMP, Arias-VasquezA, HoogmanM, MostertJC, et al.2015. Lower white matter microstructure in the superior longitudinal fasciculus is associated with increased response time variability in adults with attention-deficit/hyperactivity disorder. J Psychiatry Neurosci, 40:344–351.
93.
YueQ, MartinRC, Fischer-BaumS, Ramos-NunezAI, YeF, DeemMW. 2017. Brain modularity mediates the relation between task complexity and performance. J Cogn Neurosci, 29:1532–1546.
94.
ZavalaB, BrittainJS, JenkinsonN, AshkanK, FoltynieT, LimousinP, et al.2013. Subthalamic nucleus local field potential activity during the Eriksen flanker task reveals a novel role for theta phase during conflict monitoring. J Neurosci, 33:14758–14766.
95.
ZentallSS, ZentallTR. 1983. Optimal stimulation: a model of disordered activity and performance in normal and deviant children. Psychol Bull, 94:446–471.
Supplementary Material
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.
