Advertisement

Experimental Brain Research

, Volume 237, Issue 2, pp 511–520 | Cite as

Transcranial Doppler sonography reveals sustained attention deficits in young adults diagnosed with ADHD

  • Tyler H. ShawEmail author
  • Timothy W. Curby
  • Kelly Satterfield
  • Samuel S. Monfort
  • Raul Ramirez
Research Article
  • 60 Downloads

Abstract

The National Institute of Mental Health has recently launched the Research Domain Criteria framework that seeks to inform clinical classification schemes by elevating the status of neuroscience research in the diagnosis of mental disorders. The current research seeks to contribute to that initiative by using a neurophysiological measure, transcranial Doppler sonography that has been shown to be sensitive to decrements in sustained attention and may provide an additional biomarker of executive dysfunction in ADHD. Twenty-seven participants performed a 12-min vigilance task while cerebral blood flow velocity (CBFV) was recorded. Thirteen participants were included in an ADHD condition if they had been formally diagnosed with ADHD. The remaining 14 participants who had never been formally diagnosed with ADHD were included in the control condition. Participants that had been diagnosed with ADHD demonstrated a steeper decrement in performance accuracy, a steeper decrement in perceptual sensitivity, and employed a more liberal response bias over time as compared to the control participants. Critically, the decrement in CBFV was steeper for participants previously diagnosed with ADHD than those who were not. Moreover, CBFV was found to better predict decreases in sensitivity and hit rate, as well as increases in liberal responding above and beyond self-reported ADHD symptoms. Results suggest that CBFV can be used to index failures of executive control in ADHD and can predict response strategy, and that the measure may provide an additional index of the sustained attention deficits associated with ADHD compared to traditional diagnostic methods.

Keywords

ADHD Transcranial Doppler TCD Vigilance Sustained attention 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Aaslid R (1986) Transcranial Doppler examination techniques. In: Aaslid R (ed) Transcranial Doppler sonography. Springer, Vienna, pp 39–59CrossRefGoogle Scholar
  2. Aaslid R (1987) Visually evoked dynamic blood flow response of the human cerebral circulation. Stroke 18:771–775CrossRefGoogle Scholar
  3. American Psychiatric Association (2013) Diagnostic and statistical manual of mental disorders, 5th edn. Author Arlington, ArlingtonCrossRefGoogle Scholar
  4. Baayen RH, Davidson DJ, Bates DM (2008) Mixed-effects modeling with crossed random effects for subjects and items. J Mem Lang 59:390–412CrossRefGoogle Scholar
  5. Babikan VL, Wechsler LR (1999) Transcranial Doppler ultrasonography, 2nd edn. Butterworth-Heinemann, BostonGoogle Scholar
  6. Barkley RA (2014) Attention-deficit hyperactivity disorder: a handbook for diagnosis and treatment. Guilford Publications, New YorkGoogle Scholar
  7. Bates DM, Maechler M, Bolker B (2012) lme4: Linear mixed-effects models using S4 classes. R package version 0.999999-0Google Scholar
  8. Becker A, Mandell AR, Tangney JP, Chrosniak LD, Shaw TH (2015) The effects of self-control on cognitive resource allocation during sustained attention: a transcranial Doppler investigation. Exp Brain Res 233:2215–2223CrossRefGoogle Scholar
  9. Boonstra AM, Oosterlaan J, Sergeant JA, Buitelaar JK (2005) Executive functioning in adult ADHD: a meta-analytic review. Psychol Med 35:1097–1108CrossRefGoogle Scholar
  10. Caplan LR, Brass LM, DeWitt LD, Adams RJ, Gomex C, Otis S, Weschler LR, von Reutern GM (1990) Transcranial Doppler ultrasound: present status. Neurology 40:696–700CrossRefGoogle Scholar
  11. Cole MW, Repovš G, Anticevic A (2014) The frontoparietal control system: a central role in mental health. Neuroscientist 20:652–664CrossRefGoogle Scholar
  12. Conners CK (1994) The Conners continuous performance test. Multi-Health Systems Inc, TorontoGoogle Scholar
  13. Cortese S, Kelly C, Chabernaud C, Proal E, Di Martino A, Milham MP, Castellanos FX (2012) Toward systems neuroscience of ADHD: a meta-analysis of 55 fMRI studies. Am J Psychiatry 169:1038–1055CrossRefGoogle Scholar
  14. Cuthbert BN (2014) The RDoC framework: facilitating transition from ICD/DSM to dimensional approaches that integrate neuroscience and psychopathology. World Psychiatry 13:28–35CrossRefGoogle Scholar
  15. Cuthbert BN, Insel TR (2013) Toward the future of psychiatric diagnosis: the seven pillars of RDoC. BMC Med 11:126CrossRefGoogle Scholar
  16. Duschek S, Schandry R (2003) Functional transcranial Doppler sonography as a tool in psychophysiological research. Psychophysiology 40:436–454CrossRefGoogle Scholar
  17. Epstein JN, Erkanli A, Conners CK, Klaric J, Costello JE, Angold A (2003) Relations between continuous performance test performance measures and ADHD behaviors. J Abnorm Child Psychol 3:543–554CrossRefGoogle Scholar
  18. Fayyad et al (2007) Cross-national prevalence and correlates of adult attention-deficit hyperactivity disorder. Br J Psychiatry 190:402–409CrossRefGoogle Scholar
  19. Frick PJ, Nigg JT (2012) Current issues in the diagnosis of attention deficit hyperactivity disorder, oppositional defiant disorder, and conduct disorder. Ann Rev Clin Psychol 8:77–107CrossRefGoogle Scholar
  20. Galinsky TL, Roger RR, Warm JS, Dember WN (1993) Psychophysical determinants of stress in sustained attention. Hum Factors 35:603–614CrossRefGoogle Scholar
  21. Harwood AE, Greenwood PM, Shaw TH (2017) Transcranial doppler sonography reveals reductions in hemispheric asymmetry in healthy older adults during vigilance. Front Aging Neurosci 9:21CrossRefGoogle Scholar
  22. Helton WS (2009) Impulsive responding and the sustained attention to response task. J Clin Exp Neuropsychol 31:39–47CrossRefGoogle Scholar
  23. Helton WS, Kern RP, Walker DR (2009) Conscious thought and the sustained attention to response task. Conscious Cogn 18:600–607CrossRefGoogle Scholar
  24. Hervey AS, Epstein JN, Curry JF (2004) Neuropsychology of adults with attention-deficit/hyperactivity disorder: a meta-analytic review. Neuropsychology 18:485CrossRefGoogle Scholar
  25. Hitchcock EM, Warm JS, Matthews G, Dember WN, Shear PK, Tripp LD, Parasuraman R (2003) Automation cueing modulates cerebral blood flow and vigilance in a simulated air traffic control task. Theor Issues Ergon Sci 4:89–112CrossRefGoogle Scholar
  26. Hockey GRJ (1997) Compensatory control in the regulation of human performance under stress and high workload: a cognitive-energetical framework. Biol Psychol 45:73–93CrossRefGoogle Scholar
  27. Insel T et al (2010) Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. Am J Psychiatry 167:748–751CrossRefGoogle Scholar
  28. Johnson A, Proctor RW (2004) Attention: theory and practice. Sage, Thousand OaksCrossRefGoogle Scholar
  29. Kapur S, Phillips AG, Insel TR (2012) Why has it taken so long for biological psychiatry to develop clinical tests and what to do about it? Mol Psychiatry 17:1174CrossRefGoogle Scholar
  30. Kessler RC et al (2010) Structure and diagnosis of adult attention-deficit/hyperactivity disorder: analysis of expanded symptom criteria from the Adult ADHD Clinical Diagnostic Scale. Arch Gen Psychiatry 67:1168–1178CrossRefGoogle Scholar
  31. Langner R, Eickhoff SB, Steinborn MB (2011) Mental fatigue modulates dynamic adaptation to perceptual demand in speeded detection. PLoS One 6:1–10CrossRefGoogle Scholar
  32. Lim J, Wu W, Wang J, Detre JA, Dinges DF, Rau H (2010) Imaging brain fatigue from sustained mental workload: An ASL perfusion study of the time-on-task effect. NeuroImage49:3426–3435Google Scholar
  33. Losier BJ, McGrath PJ, Klein RM (1996) Error patterns on the continuous performance test in non-medicated and medicated samples of children with and without ADHD: a meta-analytic review. J Child Psychol Psychiatry 37:971–987CrossRefGoogle Scholar
  34. Macmillan N, Creelman C (2004) Detection theory. Psychology Press, New YorkCrossRefGoogle Scholar
  35. Mandell A, Becker A, VanAndel A, Nelson A, Shaw TH (2015) The effect of neuroticism on vigilance performance: a transcranial Doppler investigation. Conscious Cogn 36:19–26CrossRefGoogle Scholar
  36. Matthews G, Joyner L, Gilliland K, Campbell SE, Huggins J, Falconer S (1999) Validation of a comprehensive stress state questionnaire: towards a state “big three”? In: Mervielde I, Deary IJ, De Fruyt F, Ostendorf F (eds) Personality psychology in Europe, vol 7. Tilburg University Press, Tilburg, pp 335–350Google Scholar
  37. Matthews G, Campbell SE, Falconer S, Joyner L, Huggins J, Gilliland K, Grier R, Warm JS (2002) Fundamental dimensions of subjective state in performance settings: task engagement, distress and worry. Emotion 2:315–340CrossRefGoogle Scholar
  38. Matthews G, Warm JS, Reinerman-Jones LE, Langheim LK, Guznov S, Shaw TH, Finomore VS (2011) The functional fidelity of individual differences research: the case for context-matching. Theor Issues Ergon Sci 12:435–450CrossRefGoogle Scholar
  39. Matthews G, Warm JS, Shaw TH, Finomore VS (2014) Predicting battlefield vigilance: a multivariate approach to assessment of attentional resources. Ergonomics 57:856–875CrossRefGoogle Scholar
  40. McGee RA, Clark SE, Symons DK (2000) Does the conners’ continuous performance test aid in ADHD diagnosis? J Abnorm Child Psychol 28:415–424CrossRefGoogle Scholar
  41. McGrath et al (2013) Toward a neuroimaging treatment selection biomarker for major depressive disorder. JAMA Psychiatry 70:821–829CrossRefGoogle Scholar
  42. Norman DA, Bobrow DG (1975) On data-limited and resource limited processes. Cogn Psychol 7:44–64CrossRefGoogle Scholar
  43. Parasuraman R (1979) Memory load and event rate control sensitivity decrements in sustained attention. Science 205:924–927CrossRefGoogle Scholar
  44. Parasuraman R (1984) Sustained attention in detection and discrimination. In: Parasuraman R, Davis DR (eds) Varieties of attention. Academic Press, New York, pp 243–271Google Scholar
  45. Parasuraman R (2009) Assaying individual differences in cognition with molecular genetics: theory and application. Theor Issues Ergon Sci 10:399–416CrossRefGoogle Scholar
  46. Parasuraman R, Rizzo M (2007) Neuroergonomics: the brain at work. Oxford University Press, New YorkGoogle Scholar
  47. Parasuraman R, Warm JS, Dember WN (1987) Vigilance: taxonomy and utility. Ergonomics and human factors. Springer, New York, pp 11–32CrossRefGoogle Scholar
  48. Parasuraman R, Warm JS, See JE (1998) The attentive brain. MIT Press, Cambridge, pp 221–256Google Scholar
  49. Pinheiro JC, Bates DM (2000) Mixed-effects models in S and S-PLUS. Springer Science and Business Media, New YorkCrossRefGoogle Scholar
  50. Posner MI, Raichle M (1993) Images of mind. McGraw-Hill, New YorkGoogle Scholar
  51. Proctor RW, Vu KPL (2012) Human information processing. Encyclopedia of the science of learning. Springer, New York, pp 1458–1460Google Scholar
  52. R Core Team (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/. Accessed 2016
  53. Raz A, Lieber B, Soliman F, Buhle J, Posner J, Peterson BS, Posner MI (2005) Ecological nuances in functional magnetic resonance imaging (fMRI): psychological stressors, posture, and hydrostatics. Neuroimage 25:1–7CrossRefGoogle Scholar
  54. Riccio CA, Reynolds CR, Lowe PA (2001) Clinical applications of continuous performance tests: measuring attention and impulsive responding in children and adults. Wiley, New YorkGoogle Scholar
  55. Roth RM, Saykin AJ (2004) Executive dysfunction in attention-deficit/hyperactivity disorder: cognitive and neuroimaging findings. Psychiatr Clin N Am 27:83–96CrossRefGoogle Scholar
  56. Satterthwaite FE (1946) An approximate distribution of estimates of variance components. Biom Bull 2(6):110–114CrossRefGoogle Scholar
  57. Schmidt et al (1999) Determination of cognitive hemispheric lateralization by ‘‘functional’’ transcranial Doppler cross-validated by functional MRI. Stroke 30:939–945CrossRefGoogle Scholar
  58. Schnittger C, Johannes S, Arnavaz A, Münte TF (1997) Relation of cerebral blood flow velocity and level of vigilance in humans. NeuroReport 8:1637–1639CrossRefGoogle Scholar
  59. Scolari M, Seidl-Rathkopf KN, Kastner S (2015) Functions of the human frontoparietal attention network: evidence from neuroimaging. Curr Opin Behav Sci 1:32–39CrossRefGoogle Scholar
  60. Shaw TH, Warm JS, Finomore V, Tripp L, Matthews G, Weiler E, Parasuraman R (2009) Effects of sensory modality on cerebral blood flow velocity during vigilance. Neurosci Lett 461:207–211CrossRefGoogle Scholar
  61. Shaw T, Emfield A, Garcia A, de Visser E, Miller C, Parasuraman R, Fern L (2010a) Evaluating the benefits and potential costs of automation delegation for supervisory control of multiple UAVs. In: Proc of the hum fac and erg soc. Los Angeles, CA: SAGE PublicationsGoogle Scholar
  62. Shaw TH, Matthews G, Warm JS, Finomore VS, Silverman L, Costa PT (2010b) Individual differences in vigilance: personality, ability and states of stress. J Res Pers 44:297–308CrossRefGoogle Scholar
  63. Shaw TH, Finomore VS, Warm JS, Matthews G (2012) Effects of regular or irregular event schedules on cerebral hemovelocity during a sustained attention task. J Clin Exp Neuropsychol 34:57–66CrossRefGoogle Scholar
  64. Shaw TH, Satterfield K, Ramirez R, Finomore V (2013) Using cerebral hemovelocity to measure workload during a spatialized auditory vigilance task in novice and experienced observers. Ergonomics 56:1251–1263CrossRefGoogle Scholar
  65. Shaw TH, Nguyen C, Satterfield K, Ramirez R, McKnight PE (2016) Cerebral hemovelocity reveals differential resource allocation strategies for extraverts and introverts during vigilance. Exp Brain Res 234:577–585CrossRefGoogle Scholar
  66. Shingledecker S, Weldon DE, Behymer K, Simpkins B, Lerner E, Warm J, Matthews G, Finomore V, Shaw T, Murphy JS (2009) Measuring vigilance abilities to enhance combat identification performance. In: Andrews DH, Herz RP, Wolf MB (eds) Human factors in combat identification performanc. Ashgate Publishing, Aldershot, UK, pp 47–65Google Scholar
  67. Stroobant N, Vingerhoets G (2000) Transcranial Doppler ultrasonography monitoring of cerebral hemodynamics during performance of cognitive tasks: a review. Neuropsychol Rev 10:213–231CrossRefGoogle Scholar
  68. Temple JG, Warm JS, Dember WN, Jones KS, LaGrange CM, Matthews G (2000) The effects of signal salience and caffeine on performance, workload, and stress in an abbreviated vigilance task. Hum Factors 42:183–194CrossRefGoogle Scholar
  69. Toplak ME, PitchA FloraDB, Iwenofu L, Ghelani K, Jain U, Tannock R (2009) The unity and diversity of inattention and hyperactivity/impulsivity in ADHD: evidence for a general factor with separable dimensions. J Abnorm Child Psychol 37:1137–1150CrossRefGoogle Scholar
  70. Tulving E, Kapur S, Craik FI, Moscovitch M, Houle S (1994) Hemispheric encoding/retrieval asymmetry in episodic memory: positron emission tomography findings. Proc Natl Acad Sci 91:2016–2020CrossRefGoogle Scholar
  71. Warm JS, Parasuraman R, Matthews G (2008) Vigilance requires hard mental work and is stressful. Hum Factors 50:433–441CrossRefGoogle Scholar
  72. Warm JS, Matthews G, Parasuraman R (2009) Cerebral hemodynamics and vigilance performance. Milit Psychol 21(Suppl. 1):S75–S100Google Scholar
  73. Wiggins MW (2011) Vigilance decrement during a simulated general aviation flight. Appl Cogn Psychol 25:229–235CrossRefGoogle Scholar
  74. Willcutt EG, Doyle AE, Nigg JT, Faraone SV, Pennington BF (2005) Validity of the executive function theory of attention-deficit/hyperactivity disorder: a meta-analytic review. Biol Psychiatry 57:1336–1346CrossRefGoogle Scholar
  75. Woods SP, Lovejoy DW, Ball JD (2002) Neuropsychological characteristics of adults with ADHD: a comprehensive review of initial studies. Clin Neuropsychol 16:12–34CrossRefGoogle Scholar
  76. Young S (2004) The YAQ-S and YAQ-I: the development of self and informant questionnaires reporting on current adult ADHD symptomatology, comorbid and associated problems. Pers Individ Differ 36:1211–1223CrossRefGoogle Scholar
  77. Young S, Gudjonsson GH (2005) Neuropsychological correlates of the YAQ-S and YAQ-I self-and informant-reported ADHD symptomatology, emotional and social problems and delinquent behaviour. Br J Clin Psychol 44:47–57CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of PsychologyGeorge Mason UniversityFairfaxUSA

Personalised recommendations