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Using the Diffusion Model to Explain Cognitive Deficits in Attention Deficit Hyperactivity Disorder

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Abstract

Slow, variable, and error-prone performance on speeded reaction time (RT) tasks has been well documented in childhood ADHD, but equally well documented is the context-dependent nature of those deficits, particularly with respect to event rate. As event rates increase (or, as the interstimulus intervals become shorter), RTs decrease, a pattern of performance that has long been interpreted as evidence that cognitive deficits in ADHD are a downstream consequence of a fundamental difficulty in the regulation of arousal to meet task demands. We test the extent to which this is a misinterpretation of the data that occurs when RT and accuracy are considered separately, as is common in neurocognitive research. In two samples of children aged 8–10 with (N = 97; 33 girls) and without (N = 39; 26 girls) ADHD, we used the diffusion model, an influential computational model of RT, to examine the effect of event rate on inhibitory control in a go-no-go task. Contrary to longstanding belief, we found that fast event rates slowed the rate at which children with ADHD accumulated evidence to make a decision to “no-go”, as indexed by drift rate. This in turn resulted in a higher proportion of failed inhibits, and occurred despite increased task engagement, as reflected by changes in the starting point of the decision process. Thus, although faster event rates increased task engagement among children with ADHD, the increased engagement was unable to counteract the concurrent slowing of processing speed to “no-go” decisions. Implications for theoretical models of ADHD and treatments are discussed.

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References

  • Alderson, R. M., Rapport, M. D., & Kofler, M. J. (2007). Attention-deficit/hyperactivity disorder and behavioral inhibition: a meta-analytic review of the stop-signal paradigm. Journal of Abnormal Child Psychology, 35, 745–758. doi:10.1007/s10802-007-9131-6.

    Article  PubMed  Google Scholar 

  • Andreou, P., Neale, B. M., Chen, W., Christiansen, H., Gabriels, I., Heise, A., . . . Kuntsi, J. (2007). Reaction time performance in ADHD: Improvement under fast-incentive condition and familial effects. Psychological Medicine, 37, 1703–1715. 10.1017/s0033291707000815

  • Aron, A. R. (2011). From reactive to proactive and selective control: developing a richer model for stopping inappropriate responses. Biological Psychiatry, 69, E55–E68. doi:10.1016/j.biopsych.2010.07.024.

    Article  PubMed  Google Scholar 

  • Barkley, R. A. (1997). Behavioral inhibition, sustained attention, and executive functions: constructing a unifying theory of ADHD. Psychological Bulletin, 121, 65–94.

    Article  PubMed  Google Scholar 

  • Block, R. A., Hancock, P. A., & Zakay, D. (2010). How cognitive load affects duration judgments: a meta-analytic review. Acta Psychologica, 134, 330–343. doi:10.1016/j.actpsy.2010.03.006.

    Article  PubMed  Google Scholar 

  • Bogacz, R., Wagenmakers, E. J., Forstmann, B. U., & Nieuwenhuis, S. (2010). The neural basis of the speed-accuracy tradeoff. Trends in Neurosciences, 33, 10–16. doi:10.1016/j.tins.2009.09.002.

    Article  PubMed  Google Scholar 

  • Botvinick, M., & Braver, T. (2015). Motivation and cognitive control: from behavior to neural mechanism. Annual Review of Psychology, 66, 83–113. doi:10.1146/annurev-psych-010814-015044.

    Article  PubMed  Google Scholar 

  • Brown, S. W. (1997). Attentional resources in timing: Interference effects in concurrent temporal and nontemporal working memory tasks. Perception & Psychophysics, 59, 1118–1140. doi:10.3758/bf03205526.

    Article  Google Scholar 

  • Brown, A. M., & Ransom, B. R. (2007). Astrocyte glycogen and brain energy metabolism. Glia, 55, 1263–1271. doi:10.1002/glia.20557.

    Article  PubMed  Google Scholar 

  • Castellanos, F. X., & Tannock, R. (2002). Neuroscience of attention-deficit/hyperactivity disorder: the search for endophenotypes. Nature Reviews Neuroscience, 3, 617–628. doi:10.1038/nrn896.

    Article  PubMed  Google Scholar 

  • Cohen-Gilbert, J. E., Killgore, W. D. S., White, C. N., Schwab, Z. J., Crowley, D. J., Covell, M. J., . . . Silveri, M. M. (2014). Differential influence of safe versus threatening facial expressions on decision-making during an inhibitory control task in adolescence and adulthood. Developmental Science, 17, 212–223. 10.1111/desc.12123

  • Conners, K. (1997). Conners’ rating scales-revised technical manual. New York: Multi Health Systems.

    Google Scholar 

  • Droit-Volet, S., & Gautier, T. (2000). Time estimation in young children as a function of instructions and response type. Current Psychology of Cognition, 19, 263–276.

    Google Scholar 

  • DuPaul, G., Power, T., Anastopoulos, A., & Reid, R. (1998). ADHD rating scale-IV: checklists, norms, and clinical interpretation. New York: Guildford Press.

    Google Scholar 

  • Epstein, J. N., Langberg, J. M., Rosen, P. J., Graham, A., Narad, M. E., Antonini, T. N., . . . Altaye, M. (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. 10.1037/a0022155

  • Fabiano, G. A., Pelham, W. E., Jr., Coles, E. K., Gnagy, E. M., Chronis-Tuscano, A., & O’Connor, B. C. (2009). A meta-analysis of behavioral treatments for attention-deficit/hyperactivity disorder. Clinical Psychology Review, 29, 129–140. doi:10.1016/j.cpr.2008.11.001.

    Article  PubMed  Google Scholar 

  • Faraone, S. V., & Buitelaar, J. (2010). Comparing the efficacy of stimulants for ADHD in children and adolescents using meta-analysis. European Child & Adolescent Psychiatry, 19, 353–364. doi:10.1007/s00787-009-0054-3.

    Article  Google Scholar 

  • Gautier, T., & Droit-Volet, S. (2002a). Attention and time estimation in 5-and 8-year-old children: a dual-task procedure. Behavioural Processes, 58, 57–66. doi:10.1016/s0376-6357(02)00002-5.

    Article  PubMed  Google Scholar 

  • Gautier, T., & Droit-Volet, S. (2002b). Attentional distraction and time perception in children. International Journal of Psychology, 37, 27–34. doi:10.1080/00207590143000324.

    Article  Google Scholar 

  • Gomez, P., Perea, M., & Ratcliff, R. (2007). A model of the Go/No-Go task. Journal of Experimental Psychology-General, 136, 389–413. doi:10.1037/0096-3445.136.3.389.

    Article  PubMed  PubMed Central  Google Scholar 

  • Huang-Pollock, C. L., Karalunas, S. L., Tam, H., & Moore, A. N. (2012). Evaluating vigilance deficits in ADHD: a meta-analysis of CPT performance. Journal of Abnormal Psychology, 121, 360–371. doi:10.1037/a0027205.

    Article  PubMed  PubMed Central  Google Scholar 

  • Inzlicht, M., Schmeichel, B. J., & Macrae, C. N. (2014). Why self-control seems (but may not be) limited. Trends in Cognitive Sciences, 18, 127–133. doi:10.1016/j.tics.2013.12.009.

    Article  PubMed  Google Scholar 

  • Karalunas, S. L., & Huang-Pollock, C. L. (2013). Integrating impairments in reaction time and executive function using a diffusion model framework. Journal of Abnormal Child Psychology, 41, 837–850. doi:10.1007/s10802-013-9715-2.

    Article  PubMed  PubMed Central  Google Scholar 

  • Karalunas, S. L., Huang-Pollock, C. L., & Nigg, J. T. (2012). Decomposing attention-deficit/hyperactivity disorder (ADHD)-related effects in response speed and variability. Neuropsychology, 26, 684–694. doi:10.1037/a0029936.

    Article  PubMed  PubMed Central  Google Scholar 

  • Killeen, P. R. (2013). Absent without leave; a neuroenergetic theory of mind wandering. Frontiers in Psychology. doi:10.3389/fpsyg.2013.00373.

    PubMed  PubMed Central  Google Scholar 

  • Killeen, P. R., Russell, V. A., & Sergeant, J. A. (2013). A behavioral neuroenergetics theory of ADHD. Neuroscience and Biobehavioral Reviews, 37, 625–657. doi:10.1016/j.neubiorev.2013.02.011.

    Article  PubMed  Google Scholar 

  • Lahey, B. B., Applegate, B., McBurnett, K., Biederman, J., Greenhill, L., Hynd, G. W., . . . Shaffer, D. (1994). DSM-IV field trials for Attention-Deficit Hyperactivity Disorder in children and adolescents. American Journal of Psychiatry, 151, 1673–1685

  • Leite, F. P., & Ratcliff, R. (2011). What cognitive processes drive response biases? a diffusion model analysis. Judgment and Decision Making, 6, 651–687.

    Google Scholar 

  • Lijffijt, M., Kenemans, J. L., Verbaten, M. N., & van Engeland, H. (2005). A meta-analytic review of stopping performance in attention-deficit/hyperactivity disorder: Deficient inhibitory motor control? Journal of Abnormal Psychology, 114, 216–222. doi:10.1037/0021-843x.114.2.216.

    Article  PubMed  Google Scholar 

  • Logan, G. D., & Cowan, W. B. (1984). On the ability to inhibit thought and action: a theory of an act of control. Psychological Review, 91, 295–327. doi:10.1037//0033-295x.91.3.295.

    Article  Google Scholar 

  • Luman, M., Oosterlaan, J., & Sergeant, J. A. (2005). The impact of reinforcement contingencies on AD/HD: A review and theoretical appraisal. Clinical Psychology Review, 25, 183–213. doi:10.1016/j.cpr.2004.11.001.

    Article  PubMed  Google Scholar 

  • Masicampo, E. J., & Baumeister, R. F. (2008). Toward a physiology of dual-process reasoning and judgment - lemonade, willpower, and expensive rule-based analysis. Psychological Science, 19, 255–260. doi:10.1111/j.1467-9280.2008.02077.x.

    Article  PubMed  Google Scholar 

  • Metin, B., Roeyers, H., Wiersema, J. R., van der Meere, J., & Sonuga-Barke, E. (2012). A meta-analytic study of event rate effects on Go/No-Go performance in attention-deficit/hyperactivity disorder. Biological Psychiatry, 72, 990–996. doi:10.1016/j.biopsych.2012.08.023.

    Article  PubMed  Google Scholar 

  • Mulder, M. J., Wagenmakers, E. J., Ratcliff, R., Boekel, W., & Forstmann, B. U. (2012). Bias in the brain: a diffusion model analysis of prior probability and potential payoff. Journal of Neuroscience, 32, 2335–2343. doi:10.1523/jneurosci.4156-11.2012.

    Article  PubMed  Google Scholar 

  • Muraven, M., & Baumeister, R. F. (2000). Self-regulation and depletion of limited resources: does self-control resemble a muscle? Psychological Bulletin, 126, 247–259. doi:10.1037//0033-2909.126.2.247.

    Article  PubMed  Google Scholar 

  • Nigg, J. T. (2001). Is ADHD a disinhibitory disorder? Psychological Bulletin, 127, 571–598. doi:10.1037//0033-2909.127.5.571.

    Article  PubMed  Google Scholar 

  • Noreika, V., Falter, C. M., & Rubia, K. (2013). Timing deficits in attention-deficit/hyperactivity disorder (ADHD): Evidence from neurocognitive and neuroimaging studies. Neuropsychologia, 51, 235–266. doi:10.1016/j.neuropsychologia.2012.09.036.

    Article  PubMed  Google Scholar 

  • Patros, C. H. G., Alderson, R. M., Lea, S. E., Tarle, S. J., Kasper, L. J., & Hudec, K. L. (2015). Visuospatial working memory underlies choice-impulsivity in boys with attention-deficit/hyperactivity disorder. Research in Developmental Disabilities, 38, 134–144. doi:10.1016/j.ridd.2014.12.016.

    Article  PubMed  Google Scholar 

  • Pauli-Pott, U., & Becker, K. (2011). Neuropsychological basic deficits in preschoolers at risk for ADHD: A meta-analysis. Clinical Psychology Review, 31, 626–637. doi:10.1016/j.cpr.2011.02.005.

    Article  PubMed  Google Scholar 

  • Pe, M. L., Vandekerckhove, J., & Kuppens, P. (2013). A diffusion model account of the relationship between the emotional flanker task and rumination and depression. Emotion, 13, 739–747. doi:10.1037/a0031628.

    Article  PubMed  Google Scholar 

  • Pelham, W. E., Jr., & Fabiano, G. A. (2008). Evidence-based psychosocial treatments for attention-deficit/hyperactivity disorder. Journal of Clinical Child and Adolescent Psychology, 37, 184–214. doi:10.1080/15374410701818681.

    Article  PubMed  Google Scholar 

  • Philiastides, M. G., & Sajda, P. (2007). EEG-informed fMRI reveals spatiotemporal characteristics of perceptual decision making. Journal of Neuroscience, 27, 13082–13091. doi:10.1523/jneurosci.3540-07.2007.

    Article  PubMed  Google Scholar 

  • Ratcliff, R., & McKoon, G. (2008). The diffusion decision model: theory and data for two-choice decision tasks. Neural Computation, 20, 873–922. doi:10.1162/neco.2008.12-06-420.

    Article  PubMed  PubMed Central  Google Scholar 

  • Ratcliff, R., & Tuerlinckx, F. (2002). Estimating parameters of the diffusion model: approaches to dealing with contaminant reaction times and parameter variability. Psychonomic Bulletin & Review, 9, 438–481. doi:10.3758/bf03196302.

    Article  Google Scholar 

  • Ratcliff, R., & Van Dongen, H. P. A. (2011). Diffusion model for one-choice reaction-time tasks and the cognitive effects of sleep deprivation. Proceedings of the National Academy of Sciences of the United States of America, 108, 11285–11290. doi:10.1073/pnas.1100483108.

    Article  PubMed  PubMed Central  Google Scholar 

  • Ratcliff, R., Thapar, A., & McKoon, G. (2006). Aging, practice, and perceptual tasks: a diffusion model analysis. Psychology and Aging, 21, 353–371. doi:10.1037/0882-7974.21.2.353.

    Article  PubMed  PubMed Central  Google Scholar 

  • Ratcliff, R., Love, J., Thompson, C. A., & Opfer, J. E. (2012). Children Are Not like older adults: a diffusion model analysis of developmental changes in speeded responses. Child Development, 83, 367–381. doi:10.1111/j.1467-8624.2011.01683.x.

    Article  PubMed  Google Scholar 

  • Ratcliff, R., Huang-Pollock, C. L., & McKoon, G. (in press). Modeling the go/no-go task. Decision.

  • Reynolds, C., & Kamphaus, R. (1992). Behavior assessment system for children: manual. Minnesota: American Guidance Service, Inc.

    Google Scholar 

  • Rubia, K., Halari, R., Christakou, A., & Taylor, E. (2009). Impulsiveness as a timing disturbance: neurocognitive abnormalities in attention-deficit hyperactivity disorder during temporal processes and normalization with methylphenidate. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 364, 1919–1931. doi:10.1098/rstb.2009.0014.

    Article  PubMed  PubMed Central  Google Scholar 

  • Sagvolden, T., Johansen, E. B., Aase, H., & Russell, V. A. (2005). A dynamic developmental theory of attention-deficit/hyperactivity disorder (ADHD) predominantly hyperactive/impulsive and combined subtypes. Behavioral and Brain Sciences, 28, 397–468.

    Article  PubMed  Google Scholar 

  • Sanders, A. F. (1970). Some variables affecting relation between relative stimulus frequency and choice reaction time. Acta Psychologica, 33, 45. doi:10.1016/0001-6918(70)90121-6.

    Article  Google Scholar 

  • Sergeant, J. A. (2000). The cognitive-energetic model: an empirical approach to Attention-Deficit Hyperactivity Disorder. Neuroscience and Biobehavioral Reviews, 24, 7–12.

    Article  PubMed  Google Scholar 

  • Sergeant, J. A. (2005). Modeling attention-deficit/hyperactivity disorder: A critical appraisal of the cognitive-energetic model. Biological Psychiatry, 57, 1248–1255. doi:10.1016/j.bps.2004.09.010.

    Article  PubMed  Google Scholar 

  • Shaffer, D., Fisher, P., & Lucas, R. (1997). NIMH Diagnostic INterview Schedule for Children-IV. New York: Ruane Center for Early Diagnosis, Division of Child Psychiatry, Columbia University.

    Google Scholar 

  • Sonuga-Barke, E., Sergeant, J. A., Nigg, J., & Willcutt, E. (2008). Executive dysfunction and delay aversion in attention deficit hyperactivity disorder: Nosologic and diagnostic implications. Child and Adolescent Psychiatric Clinics of North America, 17, 367–384. doi:10.1016/j.chc.2007.11.008.

    Article  PubMed  Google Scholar 

  • Sonuga-Barke, E., Wiersema, J. R., van der Meere, J. J., & Roeyers, H. (2010). Context-dependent Dynamic Processes in Attention Deficit/Hyperactivity Disorder: Differentiating Common and Unique Effects of State Regulation Deficits and Delay Aversion. Neuropsychology Review, 20, 86–102. doi:10.1007/s11065-009-9115-0.

    Article  PubMed  Google Scholar 

  • Verbruggen, F., & Logan, G. D. (2008). Automatic and Controlled Response Inhibition: Associative Learning in the Go/No-Go and Stop-Signal Paradigms. Journal of Experimental Psychology-General, 137, 649–672. doi:10.1037/a0013170.

    Article  PubMed  PubMed Central  Google Scholar 

  • Verbruggen, F., Chambers, C. D., & Logan, G. D. (2013). Fictitious Inhibitory Differences: How Skewness and Slowing Distort the Estimation of Stopping Latencies. Psychological Science, 24, 352–362. doi:10.1177/0956797612457390.

    Article  PubMed  PubMed Central  Google Scholar 

  • Wagenmakers, E.-J., van der Maas, H. L. J., & Grasman, R. P. P. P. (2007). An EZ-diffusion model for response time and accuracy. Psychonomic Bulletin & Review, 14, 3–22.

    Article  Google Scholar 

  • Wechsler, D. (2003). Wechsler Intelligence Scale for Children, 4th Ed (WISC-IV) Technical and Interpretive Manual. San Antonio: Harcourt Brace.

    Google Scholar 

  • Weigard, A., & Huang-Pollock, C. L. (2014). A diffusion modeling approach to understanding contextual cueing effects in children with ADHD. Journal of Child Psychology and Psychiatry, 55, 1336–1344. doi:10.1111/jcpp.12250.

    Article  PubMed  PubMed Central  Google Scholar 

  • Weigard, A., & Huang-Pollock, C. L. (in press). Characterizing consequences of impaired monitoring of learned behavior in ADHD using a Bayesian hierarchical model of choice response time. Neuropsychology.

  • Westbrook, A., & Braver, T. S. (2015). Cognitive effort: A neuroeconomic approach. Cognitive, Affective, & Behavioral Neuroscience, 15, 395–415. doi:10.3758/s13415-015-0334-y.

    Article  Google Scholar 

  • Westbrook, A., Kester, D., & Braver, T. S. (2013). What Is the Subjective Cost of Cognitive Effort? Load, Trait, and Aging Effects Revealed by Economic Preference. Plos One, 8. doi: 10.1371/journal.pone.0068210

  • White, C. N., Ratcliff, R., Vasey, M. W., & McKoon, G. (2010). Using diffusion models to understand clinical disorders. Journal of Mathematical Psychology, 54, 39–52. doi:10.1016/j.jmp.2010.01.004.

    Article  PubMed  PubMed Central  Google Scholar 

  • White, C. N., Mumford, J. A., & Poldrack, R. A. (2012). Perceptual Criteria in the Human Brain. Journal of Neuroscience, 32, 16716–16724. doi:10.1523/jneurosci.1744-12.2012.

    Article  PubMed  Google Scholar 

  • Wiecki, T. V., Poland, J., & Frank, M. J. (2015). Model-Based Cognitive Neuroscience Approaches to Computational Psychiatry: Clustering and Classification. Clinical Psychological Science, 3, 378–399. doi:10.1177/2167702614565359.

    Article  Google Scholar 

  • Wiersema, R., van der Meere, J., Roeyers, H., Van Coster, R., & Baeyens, D. (2006). Event rate and event-related potentials in ADHD. Journal of Child Psychology and Psychiatry, 47, 560–567. doi:10.1111/j.1469-7610.2006.01592.x.

    Article  PubMed  Google Scholar 

  • Willcutt, E. G., Doyle, A., Nigg, J. T., Faraone, S. V., & Pennington, B. F. (2005). Validity of the executive function theory of attention-deficit/hyperactivity disorder: A meta-analytic review. Biological Psychiatry, 57, 1336–1346. doi:10.1016/j.biopsych.2005.02.006.

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Psychology, The Pennsylvania State University, Moore Building, University Park, PA, 16802, USA

    Cynthia Huang-Pollock, Zvi Shapiro, Alex Weigard & Hilary Galloway-Long

  2. The Department of Psychology, Ohio State University, 291 Psychology Building, Columbus, OH, 43210, USA

    Roger Ratcliff & Gail McKoon

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  1. Cynthia Huang-Pollock
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Correspondence to Cynthia Huang-Pollock.

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This work was supported in part by National Institute of Mental Health Grant R01 MH084947 to Cynthia Huang-Pollock. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health or the National Institutes of Health.

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Huang-Pollock, C., Ratcliff, R., McKoon, G. et al. Using the Diffusion Model to Explain Cognitive Deficits in Attention Deficit Hyperactivity Disorder. J Abnorm Child Psychol 45, 57–68 (2017). https://doi.org/10.1007/s10802-016-0151-y

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