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Neural substrates of behavioral variability in attention deficit hyperactivity disorder: based on ex-Gaussian reaction time distribution and diffusion spectrum imaging tractography

Published online by Cambridge University Press:  09 August 2013

H.-Y. Lin ,
S. S.-F. Gau ,
S. L. Huang-Gu ,
C.-Y. Shang ,
Y.-H. Wu  and
W.-Y. I. Tseng
H.-Y. Lin
Affiliation:
Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
S. S.-F. Gau*
Affiliation:
Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan Department of Psychiatry, National Taiwan University College of Medicine, Taipei, Taiwan Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine, Taipei, Taiwan Department of Psychology, School of Occupational Therapy, and Graduate Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
S. L. Huang-Gu
Affiliation:
Graduate Institute of Behavioral Sciences and Department of Occupational Therapy, College of Medicine, Chang Gung University, Kwei-Shan, Tao-Yuan, Taiwan
C.-Y. Shang
Affiliation:
Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan Department of Psychiatry, National Taiwan University College of Medicine, Taipei, Taiwan Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine, Taipei, Taiwan
Y.-H. Wu
Affiliation:
School of Medicine, National Taiwan University College of Medicine, Taipei, Taiwan
W.-Y. I. Tseng*
Affiliation:
Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine, Taipei, Taiwan Center for Optoelectronic Biomedicine, National Taiwan University College of Medicine, Taipei, Taiwan Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan
*
*Address for correspondence: S. S.-F. Gau, M.D., Ph.D., Department of Psychiatry, National Taiwan University Hospital and College of Medicine, No. 7, Chung-Shan South Road, Taipei 10002, Taiwan. (Email: [email protected]) [S. S.-F. Gau] (Email: [email protected]) [W.-Y. I. Tseng]
*Address for correspondence: S. S.-F. Gau, M.D., Ph.D., Department of Psychiatry, National Taiwan University Hospital and College of Medicine, No. 7, Chung-Shan South Road, Taipei 10002, Taiwan. (Email: [email protected]) [S. S.-F. Gau] (Email: [email protected]) [W.-Y. I. Tseng]
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Abstract

Background

Increased intra-individual variability (IIV) in reaction time (RT) across various tasks is one ubiquitous neuropsychological finding in attention deficit hyperactivity disorder (ADHD). However, neurobiological underpinnings of IIV in individuals with ADHD have not yet been fully delineated. The ex-Gaussian distribution has been proved to capture IIV in RT. The authors explored the three parameters [μ (mu), σ (sigma), τ (tau)] of an ex-Gaussian RT distribution derived from the Conners' continuous performance test (CCPT) and their correlations with the microstructural integrity of the frontostriatal–caudate tracts and the cingulum bundles.

Method

We assessed 28 youths with ADHD (8–17 years; 25 males) and 28 age-, sex-, IQ- and handedness-matched typically developing (TD) youths using the CCPT, Wechsler Intelligence Scale for Children, 3rd edition and magnetic resonance imaging (MRI). Microstructural integrity, indexed by generalized fractional anisotropy (GFA), was measured by diffusion spectrum imaging tractrography on a 3-T MRI system.

Results

Youths with ADHD had larger σ (s.d. of Gaussian distribution) and τ (mean of exponential distribution) and reduced GFA in four bilateral frontostriatal tracts. With increased inter-stimulus intervals of CCPT, the magnitude of greater τ in ADHD than TD increased. In ADHD youths, the cingulum bundles and frontostriatal integrity were associated with three ex-Gaussian parameters and with μ (mean of Gaussian distribution) and τ, respectively; while only frontostriatal GFA was associated with μ and τ in TD youths.

Conclusions

Our findings suggest the crucial role of the integrity of the cingulum bundles in accounting for IIV in ADHD. Involvement of different brain systems in mediating IIV may relate to a distinctive pathophysiological processing and/or adaptive compensatory mechanism.

Keywords

Attention deficit hyperactivity disordercingulumdiffusion spectrum imagingex-Gaussian distribution of reaction timefrontostriatal tractsintra-individual variabilitymicrostructural integrity
Type
Original Articles
Information
Psychological Medicine , Volume 44 , Issue 8 , June 2014 , pp. 1751 - 1764
Copyright
Copyright © Cambridge University Press 2013 

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References

Afifi, AK, Bergman, RA (1998). Functional Neuroanatomy: Text and Atlas. McGraw-Hill, Health Professions Division: New York.Google Scholar
Alexander, GE, DeLong, MR, Strick, PL (1986). Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annual Review of Neuroscience 9, 357–381.CrossRefGoogle ScholarPubMed
Andrews-Hanna, JR, Reidler, JS, Sepulcre, J, Poulin, R, Buckner, RL (2010). Functional-anatomic fractionation of the brain's default network. Neuron 65, 550–562.CrossRefGoogle ScholarPubMed
Anstey, KJ, Mack, HA, Christensen, H, Li, SC, Reglade-Meslin, C, Maller, J, Kumar, R, Dear, K, Easteal, S, Sachdev, P (2007). Corpus callosum size, reaction time speed and variability in mild cognitive disorders and in a normative sample. Neuropsychologia 45, 1911–1920.CrossRefGoogle Scholar
Balota, DA, Yap, MJ (2011). Moving beyond the mean in studies of mental chronometry: the power of response time distributional analyses. Current Directions in Psychological Science 20, 160–166.CrossRefGoogle Scholar
Beckmann, M, Johansen-Berg, H, Rushworth, MF (2009). Connectivity-based parcellation of human cingulate cortex and its relation to functional specialization. Journal of Neuroscience 29, 1175–1190.CrossRefGoogle ScholarPubMed
Bellgrove, MA, Hester, R, Garavan, H (2004). The functional neuroanatomical correlates of response variability: evidence from a response inhibition task. Neuropsychologia 42, 1910–1916.Google Scholar
Bezeau, S, Graves, R (2001). Statistical power and effect sizes of clinical neuropsychology research. Journal of Clinical and Experimental Neuropsychology 23, 399–406.CrossRefGoogle ScholarPubMed
Bunce, D, Anstey, KJ, Cherbuin, N, Burns, R, Christensen, H, Wen, W, Sachdev, PS (2010). Cognitive deficits are associated with frontal and temporal lobe white matter lesions in middle-aged adults living in the community. PLoS ONE 5, e13567.CrossRefGoogle ScholarPubMed
Bunce, D, Anstey, KJ, Christensen, H, Dear, K, Wen, W, Sachdev, P (2007). White matter hyperintensities and within-person variability in community-dwelling adults aged 60–64 years. Neuropsychologia 45, 2009–2015.Google Scholar
Burgel, U, Amunts, K, Hoemke, L, Mohlberg, H, Gilsbach, JM, Zilles, K (2006). White matter fiber tracts of the human brain: three-dimensional mapping at microscopic resolution, topography and intersubject variability. NeuroImage 29, 1092–1105.CrossRefGoogle ScholarPubMed
Bush, G, Luu, P, Posner, MI (2000). Cognitive and emotional influences in anterior cingulate cortex. Trends in Cognitive Sciences 4, 215–222.CrossRefGoogle ScholarPubMed
Buzy, WM, Medoff, DR, Schweitzer, JB (2009). Intra-individual variability among children with ADHD on a working memory task: an ex-Gaussian approach. Child Neuropsychology 15, 441–459.Google Scholar
Callaghan, P (1991). Principles of Nuclear Magnetic Resonance Microscopy. Clarendon Press: Oxford.CrossRefGoogle Scholar
Casey, BJ, Epstein, JN, Buhle, J, Liston, C, Davidson, MC, Tonev, ST, Spicer, J, Niogi, S, Millner, AJ, Reiss, A, Garrett, A, Hinshaw, SP, Greenhill, LL, Shafritz, KM, Vitolo, A, Kotler, LA, Jarrett, MA, Glover, G (2007 a). Frontostriatal connectivity and its role in cognitive control in parent–child dyads with ADHD. American Journal of Psychiatry 164, 1729–1736.CrossRefGoogle ScholarPubMed
Casey, BJ, Nigg, JT, Durston, S (2007 b). New potential leads in the biology and treatment of attention deficit-hyperactivity disorder. Current Opinion in Neurology 20, 119–124.Google Scholar
Castellanos, FX, Kelly, C, Milham, MP (2009). The restless brain: attention-deficit hyperactivity disorder, resting-state functional connectivity, and intrasubject variability. Canadian Journal of Psychiatry 54, 665–672.CrossRefGoogle ScholarPubMed
Castellanos, FX, Lee, PP, Sharp, W, Jeffries, NO, Greenstein, DK, Clasen, LS, Blumenthal, JD, James, RS, Ebens, CL, Walter, JM, Zijdenbos, A, Evans, AC, Giedd, JN, Rapoport, JL (2002). Developmental trajectories of brain volume abnormalities in children and adolescents with attention-deficit/hyperactivity disorder. Journal of the American Medical Association 288, 1740–1748.Google Scholar
Castellanos, FX, Margulies, DS, Kelly, C, Uddin, LQ, Ghaffari, M, Kirsch, A, Shaw, D, Shehzad, Z, Di Martino, A, Biswal, B, Sonuga-Barke, EJ, Rotrosen, J, Adler, LA, Milham, MP (2008). Cingulate–precuneus interactions: a new locus of dysfunction in adult attention-deficit/hyperactivity disorder. Biological Psychiatry 63, 332–337.CrossRefGoogle ScholarPubMed
Castellanos, FX, Sonuga-Barke, EJ, Scheres, A, Di Martino, A, Hyde, C, Walters, JR (2005). Varieties of attention-deficit/hyperactivity disorder-related intra-individual variability. Biological Psychiatry 57, 1416–1423.CrossRefGoogle ScholarPubMed
Chiang, W, Wang, H, Huang, S, Yeh, F, Tseng, WI (2007). Tract-specific analysis of human white matter: mean-path based method. In Proceedings of the 16th Triennial Conference for the International Society of Magnetic Resonance, Kenting, Taiwan.Google Scholar
Chong, TT, Williams, MA, Cunnington, R, Mattingley, JB (2008). Selective attention modulates inferior frontal gyrus activity during action observation. NeuroImage 40, 298–307.CrossRefGoogle ScholarPubMed
Christakou, A, Murphy, CM, Chantiluke, K, Cubillo, AI, Smith, AB, Giampietro, V, Daly, E, Ecker, C, Robertson, D, Murphy, DG, Rubia, K (2013). Disorder-specific functional abnormalities during sustained attention in youth with attention deficit hyperactivity disorder (ADHD) and with autism. Molecular Psychiatry 18, 236–244.Google Scholar
Conners, CK, Epstein, JN, Angold, A, Klaric, J (2003). Continuous performance test performance in a normative epidemiological sample. Journal of Abnormal Child Psychology 31, 555–562.CrossRefGoogle Scholar
Cubillo, A, Halari, R, Ecker, C, Giampietro, V, Taylor, E, Rubia, K (2010). Reduced activation and inter-regional functional connectivity of fronto-striatal networks in adults with childhood attention-deficit hyperactivity disorder (ADHD) and persisting symptoms during tasks of motor inhibition and cognitive switching. Journal of Psychiatric Research 44, 629–639.CrossRefGoogle ScholarPubMed
de Zeeuw, P, Mandl, RC, Hulshoff Pol, HE, van Engeland, H, Durston, S (2012 a). Decreased frontostriatal microstructural organization in attention deficit/hyperactivity disorder. Human Brain Mapping 33, 1941–1951.Google Scholar
de Zeeuw, P, Schnack, HG, van Belle, J, Weusten, J, van Dijk, S, Langen, M, Brouwer, RM, van Engeland, H, Durston, S (2012 b). Differential brain development with low and high IQ in attention-deficit/hyperactivity disorder. PLoS ONE 7, e35770.Google Scholar
Di Martino, A, Ghaffari, M, Curchack, J, Reiss, P, Hyde, C, Vannucci, M, Petkova, E, Klein, DF, Castellanos, FX (2008). Decomposing intra-subject variability in children with attention-deficit/hyperactivity disorder. Biological Psychiatry 64, 607–614.CrossRefGoogle ScholarPubMed
Doyle, AE, Willcutt, EG, Seidman, LJ, Biederman, J, Chouinard, VA, Silva, J, Faraone, SV (2005). Attention-deficit/hyperactivity disorder endophenotypes. Biological Psychiatry 57, 1324–1335.CrossRefGoogle ScholarPubMed
Epstein, JN, Brinkman, WB, Froehlich, T, Langberg, JM, Narad, ME, Antonini, TN, Shiels, K, Simon, JO, Altaye, M (2011 a). Effects of stimulant medication, incentives, and event rate on reaction time variability in children with ADHD. Neuropsychopharmacology 36, 1060–1072.CrossRefGoogle ScholarPubMed
Epstein, JN, Langberg, JM, Rosen, PJ, Graham, A, Narad, ME, Antonini, TN, Brinkman, WB, Froehlich, T, Simon, JO, Altaye, M (2011 b). 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.CrossRefGoogle ScholarPubMed
Fassbender, C, Schweitzer, JB (2006). Is there evidence for neural compensation in attention deficit hyperactivity disorder? A review of the functional neuroimaging literature. Clinical Psychology Review 26, 445–465.CrossRefGoogle ScholarPubMed
Fassbender, C, Zhang, H, Buzy, WM, Cortes, CR, Mizuiri, D, Beckett, L, Schweitzer, JB (2009). A lack of default network suppression is linked to increased distractibility in ADHD. Brain Research 1273, 114–128.Google Scholar
Fjell, AM, Westlye, LT, Amlien, IK, Walhovd, KB (2011). Reduced white matter integrity is related to cognitive instability. Journal of Neuroscience 31, 18060–18072.CrossRefGoogle ScholarPubMed
Fox, MD, Snyder, AZ, Vincent, JL, Corbetta, M, Van Essen, DC, Raichle, ME (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences USA 102, 9673–9678.CrossRefGoogle ScholarPubMed
Frazier, TW, Demaree, HA, Youngstrom, EA (2004). Meta-analysis of intellectual and neuropsychological test performance in attention-deficit/hyperactivity disorder. Neuropsychology 18, 543–555.Google Scholar
Frazier-Wood, AC, Bralten, J, Arias-Vasquez, A, Luman, M, Ooterlaan, J, Sergeant, J, Faraone, SV, Buitelaar, J, Franke, B, Kuntsi, J, Rommelse, NN (2012). Neuropsychological intra-individual variability explains unique genetic variance of ADHD and shows suggestive linkage to chromosomes 12, 13, and 17. American Journal of Medical Genetics. Part B, Neuropsychiatric Genetics 159B, 131–140.Google Scholar
Gau, SS, Shang, CY (2010). Executive functions as endophenotypes in ADHD: evidence from the Cambridge Neuropsychological Test Battery (CANTAB). Journal of Child Psychology and Psychiatry 51, 838–849.CrossRefGoogle ScholarPubMed
Geurts, HM, Grasman, RP, Verte, S, Oosterlaan, J, Roeyers, H, van Kammen, SM, Sergeant, JA (2008). Intra-individual variability in ADHD, autism spectrum disorders and Tourette's syndrome. Neuropsychologia 46, 3030–3041.CrossRefGoogle ScholarPubMed
Geurts, HM, Verte, S, Oosterlaan, J, Roeyers, H, Sergeant, JA (2005). ADHD subtypes: do they differ in their executive functioning profile? Archives of Clinical Neuropsychology 20, 457–477.CrossRefGoogle ScholarPubMed
Gilbert, SJ, Burgess, PW (2008). Executive function. Current Biology 18, R110–R114.CrossRefGoogle ScholarPubMed
Greicius, MD, Supekar, K, Menon, V, Dougherty, RF (2009). Resting-state functional connectivity reflects structural connectivity in the default mode network. Cerebral Cortex 19, 72–78.Google Scholar
Halperin, JM, Schulz, KP (2006). Revisiting the role of the prefrontal cortex in the pathophysiology of attention-deficit/hyperactivity disorder. Psychological Bulletin 132, 560–581.Google Scholar
Hamilton, LS, Levitt, JG, O'Neill, J, Alger, JR, Luders, E, Phillips, OR, Caplan, R, Toga, AW, McCracken, J, Narr, KL (2008). Reduced white matter integrity in attention-deficit hyperactivity disorder. Neuroreport 19, 1705–1708.Google Scholar
Hartikainen, KM, Knight, RT (2003). Lateral and orbital prefrontal cortex contributions to attention. In Detection of Change: Event-Related Potential and fMRI Findings (ed. Polich, J.), pp. 99–116. Springer: New York.Google Scholar
Hervey, AS, Epstein, JN, Curry, JF, Tonev, S, Arnold, LE, Conners, CK, Hinshaw, SP, Swanson, JM, Hechtman, L (2006). Reaction time distribution analysis of neuropsychological performance in an ADHD sample. Child Neuropsychology 12, 125–140.CrossRefGoogle Scholar
Honey, CJ, Sporns, O, Cammoun, L, Gigandet, X, Thiran, JP, Meuli, R, Hagmann, P (2009). Predicting human resting-state functional connectivity from structural connectivity. Proceedings of the National Academy of Sciences USA 106, 2035–2040.CrossRefGoogle ScholarPubMed
Jackson, JD, Balota, DA, Duchek, JM, Head, D (2012). White matter integrity and reaction time intraindividual variability in healthy aging and early-stage Alzheimer disease. Neuropsychologia 50, 357–366.Google Scholar
Kelly, AM, Uddin, LQ, Biswal, BB, Castellanos, FX, Milham, MP (2008). Competition between functional brain networks mediates behavioral variability. NeuroImage 39, 527–537.CrossRefGoogle ScholarPubMed
Klein, C, Wendling, K, Huettner, P, Ruder, H, Peper, M (2006). Intra-subject variability in attention-deficit hyperactivity disorder. Biological Psychiatry 60, 1088–1097.CrossRefGoogle ScholarPubMed
Konrad, A, Dielentheis, TF, El Masri, D, Bayerl, M, Fehr, C, Gesierich, T, Vucurevic, G, Stoeter, P, Winterer, G (2010). Disturbed structural connectivity is related to inattention and impulsivity in adult attention deficit hyperactivity disorder. European Journal of Neuroscience 31, 912–919.Google Scholar
Konrad, A, Dielentheis, TF, Masri, DE, Dellani, PR, Stoeter, P, Vucurevic, G, Winterer, G (2012). White matter abnormalities and their impact on attentional performance in adult attention-deficit/hyperactivity disorder. European Archives of Psychiatry and Clinical Neuroscience 262, 351–360.CrossRefGoogle ScholarPubMed
Konrad, K, Eickhoff, SB (2010). Is the ADHD brain wired differently? A review on structural and functional connectivity in attention deficit hyperactivity disorder. Human Brain Mapping 31, 904–916.Google Scholar
Kringelbach, ML (2005). The human orbitofrontal cortex: linking reward to hedonic experience. Nature Reviews Neuroscience 6, 691–702.Google Scholar
Kuntsi, J, Klein, C (2012). Intraindividual variability in ADHD and its implications for research of causal links. Current Topics in Behavioral Neurosciences 9, 67–91.Google Scholar
Lacouture, Y, Cousineau, D (2008). How to use MATLAB to fit the ex-Gaussian and other probability functions to a distribution of response times. Tutorials in Quantitative Methods for Psychology 4, 35–45.Google Scholar
Lahey, BB, Pelham, WE, Loney, J, Lee, SS, Willcutt, E (2005). Instability of the DSM-IV subtypes of ADHD from preschool through elementary school. Archives of General Psychiatry 62, 896–902.CrossRefGoogle ScholarPubMed
Leth-Steensen, C, Elbaz, ZK, Douglas, VI (2000). Mean response times, variability, and skew in the responding of ADHD children: a response time distributional approach. Acta Psychologica 104, 167–190.CrossRefGoogle ScholarPubMed
Levy, BJ, Wagner, AD (2011). Cognitive control and right ventrolateral prefrontal cortex: reflexive reorienting, motor inhibition, and action updating. Annals of the New York Academy of Sciences 1224, 40–62.CrossRefGoogle ScholarPubMed
Liddle, EB, Hollis, C, Batty, MJ, Groom, MJ, Totman, JJ, Liotti, M, Scerif, G, Liddle, PF (2011). Task-related default mode network modulation and inhibitory control in ADHD: effects of motivation and methylphenidate. Journal of Child Psychology and Psychiatry 52, 761–771.CrossRefGoogle ScholarPubMed
Liston, C, Cohen, MM, Teslovich, T, Levenson, D, Casey, BJ (2011). Atypical prefrontal connectivity in attention-deficit/hyperactivity disorder: pathway to disease or pathological end point? Biological Psychiatry 69, 1168–1177.CrossRefGoogle ScholarPubMed
Liston, C, Watts, R, Tottenham, N, Davidson, MC, Niogi, S, Ulug, AM, Casey, BJ (2006). Frontostriatal microstructure modulates efficient recruitment of cognitive control. Cerebral Cortex 16, 553–560.Google Scholar
MacDonald, SW, Li, S, Backman, L (2009). Neural underpinnings of within-person variability in cognitive functioning and aging. Psychology and Aging 24, 792–808.CrossRefGoogle Scholar
MacDonald, SW, Nyberg, L, Backman, L (2006). Intra-individual variability in behavior: links to brain structure, neurotransmission and neuronal activity. Trends in Neurosciences 29, 474–480.Google Scholar
Makris, N, Buka, SL, Biederman, J, Papadimitriou, GM, Hodge, SM, Valera, EM, Brown, AB, Bush, G, Monuteaux, MC, Caviness, VS, Kennedy, DN, Seidman, LJ (2008). Attention and executive systems abnormalities in adults with childhood ADHD: A DT-MRI study of connections. Cerebral Cortex 18, 1210–1220.CrossRefGoogle ScholarPubMed
Manoach, DS (2003). Prefrontal cortex dysfunction during working memory performance in schizophrenia: reconciling discrepant findings. Schizophrenia Research 60, 285–298.Google Scholar
Mars, RB, Grol, MJ (2007). Dorsolateral prefrontal cortex, working memory, and prospective coding for action. Journal of Neuroscience 27, 1801–1802.CrossRefGoogle ScholarPubMed
Miller, EK, Cohen, JD (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience 24, 167–202.Google Scholar
Moy, G, Millet, P, Haller, S, Baudois, S, de Bilbao, F, Weber, K, Lovblad, K, Lazeyras, F, Giannakopoulos, P, Delaloye, C (2011). Magnetic resonance imaging determinants of intraindividual variability in the elderly: combined analysis of grey and white matter. Neuroscience 186, 88–93.CrossRefGoogle ScholarPubMed
Murtha, S, Cismaru, R, Waechter, R, Chertkow, H (2002). Increased variability accompanies frontal lobe damage in dementia. Journal of the International Neuropsychological Society 8, 360–372.Google Scholar
Nakao, T, Radua, J, Rubia, K, Mataix-Cols, D (2011). Gray matter volume abnormalities in ADHD: voxel-based meta-analysis exploring the effects of age and stimulant medication. American Journal of Psychiatry 168, 1154–1163.CrossRefGoogle ScholarPubMed
Nezamzadeh, M, Wedeen, VJ, Wang, RP, Zhang, Y, Zhan, W, Young, K, Meyerhoff, DJ, Weiner, MW, Schuff, N (2010). In-vivo investigation of the human cingulum bundle using the optimization of MR diffusion spectrum imaging. European Journal of Radiology 75, E29–E36.CrossRefGoogle ScholarPubMed
Oldfield, RC (1971). The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9, 97–113.CrossRefGoogle ScholarPubMed
Pasini, A, Paloscia, C, Alessandrelli, R, Porfirio, MC, Curatolo, P (2007). Attention and executive functions profile in drug naive ADHD subtypes. Brain and Development 29, 400–408.CrossRefGoogle ScholarPubMed
Pavuluri, MN, Yang, S, Kamineni, K, Passarotti, AM, Srinivasan, G, Harral, EM, Sweeney, JA, Zhou, XJ (2009). Diffusion tensor imaging study of white matter fiber tracts in pediatric bipolar disorder and attention-deficit/hyperactivity disorder. Biological Psychiatry 65, 586–593.Google Scholar
Peterson, BS, Potenza, MN, Wang, Z, Zhu, H, Martin, A, Marsh, R, Plessen, KJ, Yu, S (2009). An fMRI study of the effects of psychostimulants on default-mode processing during Stroop task performance in youths with ADHD. American Journal of Psychiatry 166, 1286–1294.Google Scholar
Reese, TG, Heid, O, Weisskoff, RM, Wedeen, VJ (2003). Reduction of eddy-current-induced distortion in diffusion MRI using a twice-refocused spin echo. Magnetic Resonance in Medicine 49, 177–182.Google Scholar
Rommelse, NN, Altink, ME, Oosterlaan, J, Beem, L, Buschgens, CJ, Buitelaar, J, Sergeant, JA (2008). Speed, variability, and timing of motor output in ADHD: which measures are useful for endophenotypic research? Behavior Genetics 38, 121–132.Google Scholar
Rubia, K, Smith, AB, Brammer, MJ, Taylor, E (2007). Temporal lobe dysfunction in medication-naive boys with attention-deficit/hyperactivity disorder during attention allocation and its relation to response variability. Biological Psychiatry 62, 999–1006.Google Scholar
Schmahmann, JD, Pandya, DN, Wang, R, Dai, G, D'Arceuil, HE, de Crespigny, AJ, Wedeen, VJ (2007). Association fibre pathways of the brain: parallel observations from diffusion spectrum imaging and autoradiography. Brain 130, 630–653.Google Scholar
Sergeant, J, van der Meere, J (1990). Additive factor method applied to psychopathology with special reference to childhood hyperactivity. Acta Psychologica 74, 277–295.CrossRefGoogle ScholarPubMed
Shang, CY, Wu, YH, Gau, SS, Tseng, WY (2012). Disturbed microstructural integrity of the frontostriatal fiber pathways and executive dysfunction in children with attention deficit hyperactivity disorder. Psychological Medicine 43, 1093–1107.Google Scholar
Simmonds, DJ, Fotedar, SG, Suskauer, SJ, Pekar, JJ, Denckla, MB, Mostofsky, SH (2007). Functional brain correlates of response time variability in children. Neuropsychologia 45, 2147–2157.CrossRefGoogle ScholarPubMed
Sonuga-Barke, EJ, Castellanos, FX (2007). Spontaneous attentional fluctuations in impaired states and pathological conditions: a neurobiological hypothesis. Neuroscience and Biobehavioral Reviews 31, 977–986.Google Scholar
Spencer, SV, Hawk, LW Jr, Richards, JB, Shiels, K, Pelham, WE Jr, Waxmonsky, JG (2009). Stimulant treatment reduces lapses in attention among children with ADHD: the effects of methylphenidate on intra-individual response time distributions. Journal of Abnormal Child Psychology 37, 805–816.CrossRefGoogle ScholarPubMed
Stuss, DT, Murphy, KJ, Binns, MA, Alexander, MP (2003). Staying on the job: the frontal lobes control individual performance variability. Brain 126, 2363–2380.Google Scholar
Sun, L, Cao, Q, Long, X, Sui, M, Cao, X, Zhu, C, Zuo, X, An, L, Song, Y, Zang, Y, Wang, Y (2012). Abnormal functional connectivity between the anterior cingulate and the default mode network in drug-naive boys with attention deficit hyperactivity disorder. Psychiatry Research 201, 120–127.Google Scholar
Suskauer, SJ, Simmonds, DJ, Caffo, BS, Denckla, MB, Pekar, JJ, Mostofsky, SH (2008). fMRI of intrasubject variability in ADHD: anomalous premotor activity with prefrontal compensation. Journal of the American Academy of Child and Adolescent Psychiatry 47, 1141–1150.CrossRefGoogle ScholarPubMed
Tamm, L, Narad, ME, Antonini, TN, O'Brien, KM, Hawk, LW Jr, Epstein, JN (2012). Reaction time variability in ADHD: a review. Neurotherapeutics 9, 500–508.CrossRefGoogle ScholarPubMed
Tamnes, CK, Fjell, AM, Westlye, LT, Ostby, Y, Walhovd, KB (2012). Becoming consistent: developmental reductions in intraindividual variability in reaction time are related to white matter integrity. Journal of Neuroscience 32, 972–982.Google Scholar
Tuch, DS (2004). Q-ball imaging. Magnetic Resonance in Medicine 52, 1358–1372.Google Scholar
Uebel, H, Albrecht, B, Asherson, P, Borger, NA, Butler, L, Chen, W, Christiansen, H, Heise, A, Kuntsi, J, Schafer, U, Andreou, P, Manor, I, Marco, R, Miranda, A, Mulligan, A, Oades, RD, van der Meere, J, Faraone, SV, Rothenberger, A, Banaschewski, T (2010). Performance variability, impulsivity errors and the impact of incentives as gender-independent endophenotypes for ADHD. Journal of Child Psychology and Psychiatry 51, 210–218.Google Scholar
Ullen, F, Forsman, L, Blom, O, Karabanov, A, Madison, G (2008). Intelligence and variability in a simple timing task share neural substrates in the prefrontal white matter. Journal of Neuroscience 28, 4238–4243.CrossRefGoogle Scholar
Ulrich, R, Miller, J (1994). Effects of truncation on reaction time analysis. Journal of Experimental Psychology: General 123, 34–80.Google Scholar
Valera, EM, Faraone, SV, Murray, KE, Seidman, LJ (2007). Meta-analysis of structural imaging findings in attention-deficit/hyperactivity disorder. Biological Psychiatry 61, 1361–1369.CrossRefGoogle ScholarPubMed
van den Heuvel, M, Mandl, R, Luigjes, J, Hulshoff Pol, H (2008). Microstructural organization of the cingulum tract and the level of default mode functional connectivity. Journal of Neuroscience 28, 10844–10851.CrossRefGoogle ScholarPubMed
van der Oord, S, Prins, PJ, Oosterlaan, J, Emmelkamp, PM (2008). Treatment of attention deficit hyperactivity disorder in children. Predictors of treatment outcome. European Child and Adolescent Psychiatry 17, 73–81.CrossRefGoogle ScholarPubMed
van Ewijk, H, Heslenfeld, DJ, Zwiers, MP, Buitelaar, JK, Oosterlaan, J (2012). Diffusion tensor imaging in attention deficit/hyperactivity disorder: a systematic review and meta-analysis. Neuroscience and Biobehavioral Reviews 36, 1093–1106.Google Scholar
van Noordt, SJ, Segalowitz, SJ (2012). Performance monitoring and the medial prefrontal cortex: a review of individual differences and context effects as a window on self-regulation. Frontiers in Human Neuroscience 6, 197.Google Scholar
Vaurio, RG, Simmonds, DJ, Mostofsky, SH (2009). Increased intra-individual reaction time variability in attention-deficit/hyperactivity disorder across response inhibition tasks with different cognitive demands. Neuropsychologia 47, 2389–2396.CrossRefGoogle ScholarPubMed
Vogt, BA (2009). Cingulate Neurobiology and Disease. Oxford University Press: New York.Google Scholar
Walhovd, KB, Fjell, AM (2007). White matter volume predicts reaction time instability. Neuropsychologia 45, 2277–2284.CrossRefGoogle ScholarPubMed
Wedeen, VJ, Hagmann, P, Tseng, WY, Reese, TG, Weisskoff, RM (2005). Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging. Magnetic Resonance Medicine 54, 1377–1386.Google Scholar
Wedeen, VJ, Wang, RP, Schmahmann, JD, Benner, T, Tseng, WY, Dai, G, Pandya, DN, Hagmann, P, D'Arceuil, H, de Crespigny, AJ (2008). Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers. NeuroImage 41, 1267–1277.Google Scholar
Weissman, DH, Roberts, KC, Visscher, KM, Woldorff, MG (2006). The neural bases of momentary lapses in attention. Nature Neuroscience 9, 971–978.Google Scholar
Willcutt, EG, Nigg, JT, Pennington, BF, Solanto, MV, Rohde, LA, Tannock, R, Loo, SK, Carlson, CL, McBurnett, K, Lahey, BB (2012). Validity of DSM-IV attention deficit/hyperactivity disorder symptom dimensions and subtypes. Journal of Abnormal Psychology 121, 991–1010.Google Scholar
Wood, JN, Grafman, J (2003). Human prefrontal cortex: processing and representational perspectives. Nature Reviews Neuroscience 4, 139–147.CrossRefGoogle ScholarPubMed
Wu, YH, Gau, SS, Lo, YC, Tseng, WY (2012). White matter tract integrity of frontostriatal circuit in attention deficit hyperactivity disorder: association with attention performance and symptoms. Human Brain Mapping. Published online 30 08 2012 . doi:10.1002/hbm.22169.Google ScholarPubMed
Yeh, F, Wedeen, V, Tseng, WI (2008). A recursive algorithm to decompose orientation distribution function and resolve intra-voxel fiber directions. In Proceedings of the 16th Scientific Meeting and Exhibition, Toronto, ON, Canada.Google Scholar
Yeterian, EH, Pandya, DN (1991). Prefrontostriatal connections in relation to cortical architectonic organization in rhesus monkeys. Journal of Comparative Neurology 312, 43–67.CrossRefGoogle ScholarPubMed
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