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Integrating Impairments in Reaction Time and Executive Function Using a Diffusion Model Framework

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Abstract

Using Ratcliff’s diffusion model and ex-Gaussian decomposition, we directly evaluate the role individual differences in reaction time (RT) distribution components play in the prediction of inhibitory control and working memory (WM) capacity in children with and without ADHD. Children with (n = 91, \( \overline{\mathrm{x}} \) age = 10.2 years, 67 % male) and without ADHD (n = 62, \( \overline{\mathrm{x}} \) age = 10.6 years, 46 % male) completed four tasks of WM and a stop signal reaction time (SSRT) task. Children with ADHD had smaller WM capacities and less efficient inhibitory control. Diffusion model analyses revealed that children with ADHD had slower drift rates (v) and faster non-decision times (Ter), but there were no group differences in boundary separations (a). Similarly, using an ex-Gaussian approach, children with ADHD had larger τ values than non-ADHD controls, but did not differ in μ or σ distribution components. Drift rate mediated the association between ADHD status and performance on both inhibitory control and WM capacity. τ also mediated the ADHD-executive function impairment associations; however, models were a poorer fit to the data. Impaired performance on RT and executive functioning tasks has long been associated with childhood ADHD. Both are believed to be important cognitive mechanisms to the disorder. We demonstrate here that drift rate, or the speed at which information accumulates towards a decision, is able to explain both.

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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(5), 745–758.

    Article  PubMed  Google Scholar 

  • Alderson, R. M., Rapport, M. D., Sarver, D. E., & Kofler, M. J. (2008). Adhd and behavioral inhibition: a re-examination of the stop-signal task. [Journal; Peer Reviewed Journal]. Journal of Abnormal Child Psychology: An official publication of the International Society for Research in Child and Adolescent Psychopathology, 36(7), 989–998.

    Google Scholar 

  • Balota, D. A., & Yap, M. J. (2011). Moving beyond the mean in studies of mental chronometry: the power of response time distributional analyses. Current Directions in Psychological Science, 20(3), 160–166.

    Article  Google Scholar 

  • Banaschewski, T., Yordanova, J., Kolev, V., Heinrich, H., Albrecht, B., & Rothenberger, A. (2008). Stimulus context and motor preparation in attention-deficit/hyperactivity disorder. Biological Psychology, 77(1), 53–62.

    Article  PubMed  Google Scholar 

  • Beck, J. M., Ma, W. J., Kiani, R., Hanks, T., Churchland, A. K., Roitman, J., Shadlen, M. N., Latham, P. E., & Pouget, A. (2008). Probabilistic population codes for bayesian decision making. Neuron, 60(6), 1142–1152.

    Article  PubMed  Google Scholar 

  • Biederman, J., Monuteaux, M. C., Doyle, A. E., Seidman, L. J., Wilens, T. E., Ferrero, F., Morgan, C. L., & Faraone, S. V. (2004). Impact of executive function deficits and attention-deficit/hyperactivity disorder (adhd) on academic outcomes in children. Journal of Consulting and Clinical Psychology, 72(5), 757–766.

    Article  PubMed  Google Scholar 

  • Blandon, A. Y., Calkins, S. D., Grimm, K. J., Keane, S. P., & O’Brien, M. (2010). Testing a developmental cascade model of emotional and social competence and early peer acceptance. Development and Psychopathology, 22, 737–748.

    Article  PubMed  Google Scholar 

  • Bogacz, R., Brown, E., Moehlis, J., Holmes, P., & Cohen, J. D. (2006). The physics of optimal decision making: a formal analysis of models of performance in two-alternative forced-choice tasks. Psychological Review, 113(4), 700–765.

    Article  PubMed  Google Scholar 

  • Broyd, S. J., Demanuele, C., Debener, S., Helps, S. K., James, C. J., & Sonuga-Barke, E. (2009). Default-mode brain dysfunction in mental disorders: a systematic review. Neuroscience and Biobehavioral Reviews, 33, 279–296.

    Article  PubMed  Google Scholar 

  • Buckholtz, J. W., & Meyer-Lindenberg, A. (2012). Psychopathology and the human connectome: toward a transdiagnostic model of risk for mental illness. Neuron, 74(6), 990–1004.

    Article  PubMed  Google Scholar 

  • Buzy, W. M., Medoff, D. R., & Schweitzer, J. B. (2009). Intra-individual variability among children with adhd on a working memory task: an ex-gaussian approach. Child Neuropsychology, 15(5), 441–459.

    Article  PubMed  Google Scholar 

  • Castellanos, F. X., & Tannock, R. (2002). Neuroscience of attention-deficit/hyperactivity disorder: the search for endophenotypes. Nature Reviews Neuroscience, 3(8), 617–628.

    PubMed  Google Scholar 

  • Castellanos, F. X., Sonuga-Barke, E. J. S., Scheres, A., Di Martino, A., Hyde, C., & Walters, J. R. (2005). Varieties of attention-deficit/hyperactivity disorder-related intra-individual variability. Biological Psychiatry, 57(11), 1416–1423.

    Article  PubMed  Google Scholar 

  • Castellanos, F. X., Kelly, C., & Milham, M. P. (2009). The restless brain: attention-deficit hyperactivity disorder, resting-state functional connectivity, and intrasubject variability. Canadian Journal of Psychiatry-Revue Canadienne De Psychiatrie, 54(10), 665–672.

    PubMed  Google Scholar 

  • Conners, C. K. (2001). Conners’ rating scales—revised technical manual. North Tonawanda, NY: Multi-Health Systems Inc.

  • Conway, A., Kane, M. J., Bunting, M. F., Hambrick, D. Z., Wilhelm, O., & Engle, R. W. (2005). Working memory span tasks: a methodological review and user’s guide. Psychonomic Bulletin & Review, 12(5), 769–786.

    Article  Google Scholar 

  • Deco, G., Jirsa, V., McIntosh, A. R., Sporns, O., & Kotter, R. (2009). Key role of coupling, delay, and noise in resting brain fluctuations. PNAS Proceedings of the National Academy of Sciences of the United States of America, 106(25), 10302–10307.

    Article  Google Scholar 

  • Douglas, V. I. (1999). Cognitive control processes in attention-deficit/hyperactivity disorder. In H. C. Quay & A. E. Hogan (Eds.), Handbook of disruptive behavior disorders (Vol. xiii) (pp. 105–138). NY: Kluwer Academic Publishers.

  • Epstein, J. N., Langberg, J. M., Rosen, P. J., Graham, A., Narad, M. E., Antonini, T. N., Brinkman, W. B., Froehlich, T., Simon, J. O., & 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(4), 427–441.

    Article  PubMed  Google Scholar 

  • Fair, D. A., Posner, J., Nagel, B. J., Bathula, D., Costa Dias, T. G., Mills, K. L., Blythe, M. S., Giwa, A., Schmitt, C., & Nigg, J. T. (2010). Atypical defaultnetwork connectivity in youth with attention-deficit/hyperactivity disorder. Biological Psychiatry, 68(12), 1084–1091.

    Article  PubMed  Google Scholar 

  • Fair, D., Bathula, D., Nikolas, M., & Nigg, J. T. (2012). Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with adhd. Proceedings of the National Academy of Sciences of the United States of America. doi:10.1073/pnas.1115365109.

  • Faraone, S. V., Perlis, R. H., Doyle, A., Smoller, J. W., Goralnick, J. J., Holmgren, M. A., & Sklar, P. (2005). Molecular genetics of attention-deficit/hyperactivity disorder. Biological Psychiatry, 57(11), 1313–1323.

    Google Scholar 

  • Fassbender, C., Zhang, H., Buzy, W. M., Cortese, C. R., Mizuiria, D., Beckett, L., & Schweitzer, J. B. (2009). A lack of default network suppression is linked to increased distractibility in adhd. Brain Research, 1273(1), 114–128.

    Article  PubMed  Google Scholar 

  • Frazier, T. W., Demaree, H. A., & Youngstrom, E. A. (2004). Meta-analysis of intellectual and neuropsychological test performance in attention-deficit/hyperactivity disorder. Neuropsychology, 18(3), 543–555.

    Article  PubMed  Google Scholar 

  • Froehlich, T. E., Lanphear, B., Epstein, J. N., Barbaresi, W. J., Katusic, S. K., & Kahn, R. S. (2007). Prevalence, recognition, and treatment of attention-deficit/hyperactivity disorder in a national sample of us children. Archives of Pediatrics & Adolescent Medicine, 161(9), 857–864.

    Article  Google Scholar 

  • Fry, A. F., & Hale, S. (2000). Relationships among processing speed, working memory, and fluid intelligence in children. Biological Psychology, 54(1–3), 1–34.

    Article  PubMed  Google Scholar 

  • Geurts, H. M., Grasman, R. P. P. P., Verté, S., Oosterlaan, J., Roeyers, H., van Kammen, S. M., & Sergeant, J. A. (2008). Intra-individual variability in adhd, autism spectrum disorders and tourette’s syndrome. Neuropsychologia, 46(13), 3030–3041.

    Article  PubMed  Google Scholar 

  • Grudnik, J. L., & Kranzler, J. H. (2001). Meta-analysis of the relationship between intelligence and inspection time. Intelligence, 29(6), 523–535.

    Article  Google Scholar 

  • Halperin, J. M., & Schulz, K. P. (2006). Revisiting the role of the prefrontal cortex in the pathophysiology of attention-deficit/hyperactivity disorder. Psychological Bulletin, 132(4), 560–581.

    Article  PubMed  Google Scholar 

  • Heekeren, H. R., Marrett, S., & Ungerleider, L. G. (2008). The neural systems that mediate human perceptual decision making. Nature Reviews Neuroscience, 9(6), 467–479.

    Article  PubMed  Google Scholar 

  • Hervey, A. S., Epstein, J. N., Curry, J. F., Tonev, S., Arnold, L. E., Conners, C. K., Hinshaw, S. P., Swanson, J. M., & Hechtman, L. (2006). Reaction time distribution analysis of neuropsychological performance in an adhd sample. Child Neuropsychology, 12(2), 125–140.

    Article  PubMed  Google Scholar 

  • Huang-Pollock, C. L., & Karalunas, S. L. (2010). Working memory demands impair skill acquisition in children with adhd. Journal of Abnormal Psychology, 119(1), 174–185.

    Article  PubMed  Google Scholar 

  • Huang-Pollock, C. L., Karalunas, S. L., Moore, A., & Tam, H. (2011). Working memory subsystems and their contribution to working memory deficits in children with adhd. Poster presented at the biennial meeting of the International Society for Research in Child and Adolescent Psychopathology, Chicago, IL.

  • 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(2), 360–371.

    Article  PubMed  Google Scholar 

  • Hurks, P. P. M., Adam, J. J., Hendriksen, J. G. M., Vles, J. S. H., Feron, F. J. M., Kalff, A. C., Kroes, M., Steyaert, J., Crolla, I. F. A. M., van Zeben, T. M. C. B., & Jolles, J. (2005). Controlled visuomotor preparation deficits in attention-deficit/hyperactivity disorder. Neuropsychology, 19(1), 66–76.

    Article  PubMed  Google Scholar 

  • Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., Sanislow, C., & Wang, P. (2010). Research domain criteria (rdoc): toward a new classification framework for research on mental disorders. The American Journal of Psychiatry, 167(7), 748–751.

    Article  PubMed  Google Scholar 

  • Kail, R. (2007). Longitudinal evidence that increases in processing speed and working memory enhance children’s reasoning. Psychological Science, 18(4), 312–313.

    Article  PubMed  Google Scholar 

  • Karalunas, S. L., Huang-Pollock, C. L., & Nigg, J. T. (2012). Decomposing adhd-related effects in response speed and variability. Neuropsychology, 26(6), 684–694.

    Article  PubMed  Google Scholar 

  • Klimkeit, E. I., Mattingley, J. B., Sheppard, D. M., Lee, P., & Bradshaw, J. L. (2005). Motor preparation, motor execution, attention, and executive functions in attention deficit/hyperactivity disorder (adhd). Child Neuropsychology, 11(2), 153–173.

    Article  PubMed  Google Scholar 

  • Kühn, S., Schmiedek, F., Schott, B., Ratcliff, R., Heinze, H.-J., Düzel, E., Lindenberger, U., & Lövden, M. (2011). Brain areas consistently linked to individual differences in perceptual decision-making in younger as well as older adults before and after training. Journal of Cognitive Neuroscience, 23(9), 2147–2158.

    Article  PubMed  Google Scholar 

  • Kuntsi, J., & Stevenson, J. (2001). Psychological mechanisms in hyperactivity: Ii the role of genetic factors. Journal of Child Psychology and Psychiatry, 42(2), 211–219.

    Article  PubMed  Google Scholar 

  • Kuntsi, J., Rogers, H., Swinard, G., Borger, N., van der Meere, J., Rijsdijk, F., & Asherson, P. (2006). Reaction time inhibition, working memory and ‘delay aversion’ performance: genetic influences and their interpretation. Psychological Medicine, 36(11), 1613–1624.

    Article  PubMed  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(1), 35–45.

    Google Scholar 

  • Lahey, B. B., Applegate, B., McBurnett, K., Biederman, J., Greenhill, L., Hynd, G. W., Barkley, R. A., Newcorn, J., Jensen, P., Richters, J., Garfinkel, B., Kerdyk, L., Frick, P. J., Ollendick, T., Perez, D., Hart, E. L., Waldman, I., & Shaffer, D. (1994). Dsm-iv field trials for attention-deficit hyperactivity disorder in children and adolescents. The American Journal of Psychiatry, 151(11), 1673–1685.

    PubMed  Google Scholar 

  • Lajoie, G., Anderson, V., Anderson, P., Tucker, A. R., Robertson, I. H., & Manly, T. (2005). Effects of methylphenidate on attention skills in children with attention deficit/hyperactivity disorder. Brain Impairment, 6(1), 21–32.

    Article  Google Scholar 

  • Leth-Steensen, C., Elbaz, Z. K., & Douglas, V. I. (2000). Mean response times, variability and skew in the responding of adhd children: a response time distributional approach. Acta Psychologica, 104(2), 167–190.

    Article  PubMed  Google Scholar 

  • Lijffijt, M., Bekker, E. M., Quik, E. H., Bakker, J., Kenemans, J. L., & Verbaten, M. N. (2004). Differences between low and high trait impulsivity are not associated with differences in inhibitory motor control. Journal of Attention Disorders, 8(1), 25–32.

    Article  PubMed  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(2), 216–222.

    Article  PubMed  Google Scholar 

  • MacDonald, S. W. S., Li, S.-C., & Bäckman, L. (2009). Neural underpinnings of within-person variability in cognitive functioning. Psychology and Aging, 24(4), 792–808.

    Article  PubMed  Google Scholar 

  • Martinussen, R., Hayden, J., Hogg-Johnson, S., & Tannock, R. (2005). A meta-analysis of working memory impairments in children with attention-deficit/hyperactivity disorder. Journal of the American Academy of Child and Adolescent Psychiatry, 44(4), 377–384.

    Article  PubMed  Google Scholar 

  • Matzke, D., & Wagenmakers, E.-J. (2009). Psychological interpretation of the ex-gaussian and shifted wald parameters: a diffusion model analysis. Psychonomic Bulletin & Review, 16(5), 798–817.

    Article  Google Scholar 

  • Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: a latent variable analysis. Cognitive Psychology, 41(1), 49–100.

    Article  PubMed  Google Scholar 

  • Mulder, M. J., Bos, D., Weusten, J. M. H., van Belle, J., van Dijk, S. C., Simen, P., van Engeland, H., & Durston, S. (2010). Basic impairments in regulating the speed-accuracy tradeoff predict symptoms of attention-deficit/hyperactivity disorder. Biological Psychiatry, 68(12), 1114–1119.

    Article  PubMed  Google Scholar 

  • Newman, M. E. J. (2006). Modularity and community structure in networks. Proceedings of the National Academy of Sciences of the United States of America, 103(23), 8577–8582.

    Article  PubMed  Google Scholar 

  • Nigg, J. T., Willcutt, E. G., Doyle, A., & Sonuga-Barke, E. J. S. (2005). Causal heterogeneity in attention-deficit/hyperactivity disorder: do we need neuropsychologically impaired subtypes? Biological Psychiatry, 57(11), 1224–1230.

    Article  PubMed  Google Scholar 

  • Philiastides, M. G., & Sajda, P. (2006). Temporal characterization of the neural correlates of perceptual decision making in the human brain. Cerebral Cortex, 16(4), 509–518.

    Article  PubMed  Google Scholar 

  • Philiastides, M. G., Ratcliff, R., & Sajda, P. (2006). Neural representation of task difficulty and decision making during perceptual categorization: a timing diagram. The Journal of Neuroscience, 26(35), 8965–8975.

    Article  PubMed  Google Scholar 

  • Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40, 879–891.

    Article  PubMed  Google Scholar 

  • Ratcliff, R. (2002). A diffusion model account of response time and accuracy in a brightness discrimination task: fitting real data and failing to fit fake but plausible data. Psychonomic Bulletin & Review, 9(2), 278–291.

    Article  Google Scholar 

  • Ratcliff, R., & McKoon, G. (2008). The diffusion decision model: theory and data for two-choice decision tasks. Neural Computation, 20(4), 873–922.

    Article  PubMed  Google Scholar 

  • Ratcliff, R., & Rouder, J. N. (1998). Modeling response times for two-choice decisions. Psychological Science, 9(5), 347–356.

    Article  Google Scholar 

  • Ratcliff, R., Cherian, A., & Segraves, M. (2003). A comparison of macaque behavior and superior colliculus neuronal activity to predictions from models of two-choice decisions. Journal of Neurophysiology, 90(3), 1392–1407.

    Article  PubMed  Google Scholar 

  • Ratcliff, R., Thapar, A., Gomez, P., & McKoon, G. (2004). A diffusion model analysis of the effects of aging in the lexical-decision task. Psychology and Aging, 19(2), 278–289.

    Article  PubMed  Google Scholar 

  • Ratcliff, R., Philiastides, M. G., & Sajda, P. (2009). Quality of evidence for perceptual decision making is indexed by trial-to-trial variability of the eeg. PNAS Proceedings of the National Academy of Sciences of the United States of America, 106(16), 6539–6544.

    Article  Google Scholar 

  • Reynolds, C., & Kamphaus, R. (2004). Behavioral assessment system for children, 2nd ed. Manual. Circle Pines, MN: AGS Publishing.

  • Rommelse, N. N., Altink, M. E., Oosterlaan, J., Beem, L., Buschgens, C. J. M., Buitelaar, J. K., & Sergeant, J. A. (2008). Speed, variability, and timing of motor output in adhd: which measures are useful for endophenotypic research. Behavior Genetics, 38(2), 121–132.

    Article  PubMed  Google Scholar 

  • Salthouse, T. A., McGuthry, K. E., & Hambrick, D. Z. (1999). A framework for analyzing and interpreting differential aging patterns: application to three measures of implicit learning. [Article]. Aging Neuropsychology and Cognition, 6(1), 1–18.

    Article  Google Scholar 

  • Sattler, J. (2008). Resource guide to accompany assessment of children: Cognitive foundations (5th ed.). San Diego: Jerome Sattler Publisher, Inc.

    Google Scholar 

  • Schachar, R., Chen, S., Logan, G., Ornstein, T. J., Crosbie, J., Ickowicz, A., & Pakulak, A. (2004). Evidence for an error monitoring deficit in attention deficit hyperactivity disorder. Journal of Abnormal Child Psychology, 32(3), 285–293.

    Article  PubMed  Google Scholar 

  • Schmiedek, F., Oberauer, K., Wilhelm, O., Süß, H.-M., & Wittmann, W. W. (2007). Individual differences in components of reaction time distributions and their relations to working memory and intelligence. Journal of Experimental Psychology. General, 136(3), 414–429.

    Article  PubMed  Google Scholar 

  • Schmiedek, F., Lövdén, M., & Lindenberger, U. (2009). On the relation of mean reaction time and intraindividual reaction time variability. Psychology and Aging, 24(4), 841–857.

    Article  PubMed  Google Scholar 

  • Sergeant, J. (2000). The cognitive-energetic model: an empirical approach to attention-deficit hyperactivity disorder. Neuroscience and Biobehavioral Reviews, 24(1), 7–12.

    Article  PubMed  Google Scholar 

  • Sergeant, J. A., & Scholten, C. A. (1985). On data limitations in hyperactivity. Journal of Child Psychology and Psychiatry, 26(1), 111–124.

    Article  PubMed  Google Scholar 

  • Sergeant, J., Oosterlaan, J., & van der Meere, J. (1999). Information processing and energetic factors in attention deficit/hyperactivity disorder. In H. Quay & A. Hogan (Eds.), Handbook of disruptive behavior disorders. NY: Kluwer Academic Publishers.

  • Sheslow, D., & Adams, W. (2003). Wide range assessment of memory and learning, 2nd ed (wraml-2): Administration and technical manual. Wilmington, DE: Wide Range.

  • Sonuga-Barke, E., & Castellanos, F. X. (2007). Spontaneous attentional fluctuations in impaired states and pathological conditions: a neurobiological hypothesis. Neuroscience and Biobehavioral Reviews, 31(7), 977–986.

    Article  PubMed  Google Scholar 

  • Spaniol, J., & Bayen, U. J. (2005). Aging and conditional probability judgments: a global matching approach. Psychology and Aging, 20(1), 165–181.

    Article  PubMed  Google Scholar 

  • Steger, J., Imhof, K., Coutts, E., Gundelfinger, R., Steinhausen, H. C., & Brandeis, D. (2001). Attentional and neuromotor deficits in adhd. Developmental Medicine and Child Neurology, 43(3), 172–179.

    PubMed  Google Scholar 

  • Suskauer, S. J., Simmonds, D. J., Caffo, B. S., Denckla, M. B., Pekar, J. J., & Mostofsky, S. H. (2008). Fmri of intrasubject variability in adhd: anomalous premotor activity with prefrontal compensation. Journal of the American Academy of Child and Adolescent Psychiatry, 47(10), 1141–1150.

    Article  PubMed  Google Scholar 

  • Thapar, A., Ratcliff, R., & McKoon, G. (2003). A diffusion model analysis of the effects of aging on letter discrimination. Psychology and Aging, 18(3), 415–429.

    Article  PubMed  Google Scholar 

  • Verbruggen, F., & Logan, G. D. (2009). Proactive adjustments of response strategies in the stop-signal paradigm. Journal of Experimental Psychology. Human Perception and Performance, 35(3), 835–854.

    Article  PubMed  Google Scholar 

  • Verbruggen, F., Logan, G., Liefooghe, B., & Vandierendonck, A. (2008). Short-term aftereffects of response inhibition: repetition priming or between-trial control adjustments. Journal of Experimental Psychology of Human Performance, 34(2), 413–426.

    Article  Google Scholar 

  • Voss, A., & Voss, J. (2007). Fast-dm: a free program for efficient diffusion model analysis. Behavior Research Methods, 39(4), 767–775.

    Article  PubMed  Google Scholar 

  • Voss, A., Rothermund, K., & Voss, J. (2004). Interpreting the parameters of the diffusion model: an empirical validation. Memory & Cognition, 32(7), 1206–1220.

    Article  Google Scholar 

  • Wagenmakers, E.-J., Grasman, R. P. P. P., & Molenaar, P. C. M. (2005). On the relation between the mean and the variance of a diffusion model response time distribution. Journal of Mathematical Psychology, 49, 195–204.

    Google Scholar 

  • Wechsler, D. (2003). Wechsler intelligence scale for children, 4th ed (wisc-iv) technical and interpretive manual. San Antonio: Harcourt Brace.

    Google Scholar 

  • Weissman, D. H., Roberts, K. C., Visscher, K. M., & Woldorff, M. G. (2006). The neural bases of momentary lapses in attention. Nature Neuroscience, 9, 971–978.

    Article  PubMed  Google Scholar 

  • Widaman, K. F. (2006). Best practices in quantitative methods for developmentalists: Iii. Missing data: what to do with or without them. Monographs of the Society for Research in Child Development, 71(3), 42–64.

    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(11), 1336–1346.

    Article  PubMed  Google Scholar 

  • Winstanley, C. A., Eagle, D. M., & Robbins, T. W. (2006). Behavioral models of impulsivity in relation to adhd: translation between clinical and preclinical studies. Clinical Psychology Review, 26(4), 379–395.

    Article  PubMed  Google Scholar 

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Acknowledgments

The project described was supported in part by R01MH084947 to Cynthia Huang-Pollock and F32MH098632 to Sarah Karalunas from the National Institutes of Mental Health. 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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Karalunas, S.L., Huang-Pollock, C.L. Integrating Impairments in Reaction Time and Executive Function Using a Diffusion Model Framework. J Abnorm Child Psychol 41, 837–850 (2013). https://doi.org/10.1007/s10802-013-9715-2

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