Cited by 20Autism Spectrum Disorder ResearchDevelopmental and Educational NeuropsychologyChild and Animal Learning Development

Using the NIH Toolbox to Assess Cognition in Adolescents and Young Adults with Autism Spectrum Disorders

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Solomon, Marjorie, Gordon, Andrew, Iosif, Ana‐Maria, Geddert, Raphael, Krug, Marie K., Mundy, Peter, Hessl, David·2021·Autism Research

Abstract

Despite the clinically significant impact of executive dysfunction on the outcomes of adolescents and young adults with autism spectrum disorders (ASD), we lack a clear understanding of its prevalence, profile, and development. To address this gap, we administered the NIH Toolbox Cognition Battery to a cross‐sectional Intelligence Quotient (IQ) case‐matched cohort with ASD (n = 66) and typical development (TD; n = 66) ages 12–22. We used a general linear model framework to examine group differences in task performance and their associations with age. Latent profile analysis (LPA) was used to identify subgroups of individuals with similar cognitive profiles. Compared to IQ case‐matched controls, ASD demonstrated poorer performance on inhibitory control (P < 0.001), cognitive flexibility (P < 0.001), episodic memory (P < 0.02), and processing speed (P < 0.001) (components of Fluid Cognition), but not on vocabulary or word reading (components of Crystallized Cognition). There was a significant positive association between age and Crystallized and Fluid Cognition in both groups. For Fluid (but not Crystallized) Cognition, ASD performed more poorly than TD at all ages. A four‐group LPA model based on subtest scores best fit the data. Eighty percent of ASD belonged to two groups that exhibited relatively stronger Crystallized versus Fluid Cognition. Attention deficits were not associated with Toolbox subtest scores, but were lowest in the group with the lowest proportion of autistic participants. Adaptive functioning was poorer in the groups with the greatest proportion of autistic participants. Autistic persons are especially impaired on Fluid Cognition, and this more flexible form of thinking remains poorer in the ASD group through adolescence. Lay Summary: A set of brief tests of cognitive functioning called the NIH Toolbox Cognition Battery was administered to adolescents and young adults with autism spectrum disorders (ASD; n = 66) and typical development (TD; n = 66) ages 12–22 years. Compared to TD, ASD showed poorer performance in inhibiting responses, acting flexibly, memorizing events, and processing information quickly (Fluid Cognition). Groups did not differ on vocabulary or word reading (Crystallized Cognition). Crystallized and Fluid Cognition increased with age in both groups, but the ASD group showed lower Fluid, but not Crystallized, Cognition than TD at all ages. A categorization analysis including all participants showed that most participants with ASD fell into one of two categories: a group characterized by poor performance across all tasks, or a group characterized by relatively stronger Crystallized compared to Fluid Cognition. Adaptive functioning was poorer for participants in these groups, which consisted of mostly individuals with ASD, while ADHD symptoms were lowest in the group with the greatest proportion of TD participants.

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  • The NIHTB-CB has been used extensively to examine neuropsychological functioning of children and adolescents with diverse clinical conditions.

    “The NIHTB-CB has been used extensively to examine the neuropsychological functioning of children and adolescents with diverse characteristics and clinical conditions.”

    From Cognitive weaknesses or impairments on the NIH toolbox cognition battery in children and adolescents: base rates in a normative sample and proposed methods for classification (2025) · cites this paper as Solomon et al., 2021

    The Introduction and Discussion describe using the NIHTB-CB to assess cognition in adolescents and young adults aged 12–22 with autism spectrum disorder and typical development. This supports its use in those groups, but the paper does not establish that it has been used extensively across children and adolescents with diverse clinical conditions. (LLM, conf=0.82)

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References 71 · Cited by 20

Research works printed but not linked: 57

  1. Akshoomoff N, Newman E, Thompson WK, McCabe C, Bloss CS, Chang L, … Jernigan TL (2014). The NIH Toolbox Cognition Battery: Results from a large normative developmental sample (PING). Neuropsychology, 28(1), 1– 10. 10.1037/neu0000001 24219608 PMC3925365 · DOI
  2. Ben Shalom D (2003). Memory in autism: Review and synthesis. Cortex, 39(4–5), 1129– 1138. 14584570
  3. Bowler D, Gaigg S, & Lind S (2011). Memory in autism: binding, self, and brain. In Roth I & Rezaie P (Eds.), Researching the autistic spectrum: Contemporary perspectives (pp. 316– 347). Cambridge, England: Cambridge University Press.
  4. Brunsdon VE, Colvert E, Ames C, Garnett T, Gillan N, Hallett V, … Happe F (2015). Exploring the cognitive features in children with autism spectrum disorder, their cotwins, and typically developing children within a population-based sample. Journal of Child Psychology and Psychiatry, 56 (8), 893– 902. 10.1111/jcpp.12362 25418509 · DOI · Paper page
  5. Brunsdon VE, & Happe F (2014). Exploring the ‘fractionation’ of autism at the cognitive level. Autism, 18(1), 17– 30. 10.1177/1362361313499456 24126870 · DOI
  6. Charman T, Jones CR, Pickles A, Simonoff E, Baird G, & Happé F (2011). Defining the cognitive phenotype of autism. Brain Research, 1380, 10– 21. 21029728
  7. Christ SE, Kester LE, Bodner KE, & Miles JH (2011). Evidence for selective inhibitory impairment in individuals with autism spectrum disorder. Neuropsychology, 25(6), 690– 701. 10.1037/a0024256 21728431 · DOI
  8. Corbett BA, Constantine LJ, Hendren R, Rocke D, & Ozonoff S (2009). Examining executive functioning in children with autism spectrum disorder, attention deficit hyperactivity disorder and typical development. Psychiatry Research, 166(2–3), 210– 222. 10.1016/j.psychres.2008.02.005 19285351 PMC2683039 · DOI · Paper page
  9. Craig F, Margari F, Legrottaglie AR, Palumbi R, De Giambattista C, & Margari L (2016). A review of executive function deficits in autism spectrum disorder and attention-deficit/hyperactivity disorder. Neuropsychiatric Disease and Treatment, 2016, 1191– 1202. 10.2147/ndt.s104620 PMC4869784 27274255 · DOI · Paper page
  10. de Vries M, Prins P, Schmand B, & Geurts H (2014). Working memory and cognitive flexibility-training for children with an autism spectrum disorder: A randomized controlled trial. Journal of Child Psychology and Psychiatry, 56(5), 566– 576. 10.1111/jcpp.12324 25256627 · DOI
  11. Diamond A (2013). Executive functions. Annual Review of Psychology, 64, 135– 168. 10.1146/annurev-psych-113011-143750 PMC4084861 23020641 · DOI · Paper page
  12. Eack SM, Hogarty SS, Greenwald DP, Litschge MY, Porton SA, Mazefsky CA, & Minshew NJ (2018). Cognitive enhancement therapy for adult autism spectrum disorder: Results of an 18-month randomized clinical trial. Autism Research, 11(3), 519– 530. 10.1002/aur.1913 29286586 PMC5867220 · DOI
  13. Ehlers S, Nyden A, Gillberg C, Sandberg AD, Dahlgren SO, Hjelmquist E, & Oden A (1997). Asperger syndrome, autism and attention disorders: A comparative study of the cognitive profiles of 120 children. Journal of Child Psychology and Psychiatry, 38(2), 207– 217. 10.1111/j.1469-7610.1997.tb01855.x 9232467 · DOI · Paper page
  14. Eriksen BA, & Eriksen CW (1974). Effects of noise letters upon identification of a target letter in a nonsearch task. Perception and Psychophysics, 16(1), 143– 149. 10.3758/Bf03203267 · DOI · Paper page
  15. Faja S, & Dawson G (2014). Performance on the dimensional change card sort and backward digit span by young children with autism without intellectual disability. Child Neuropsychology, 20(6), 692– 699. 10.1080/09297049.2013.856395 24266398 PMC4032814 · DOI
  16. Haigh SM, Walsh JA, Mazefsky CA, Minshew NJ, & Eack SM (2018). Processing speed is impaired in adults with autism spectrum disorder, and relates to social communication abilities. Journal of Autism and Developmental Disorders, 48(8), 2653– 2662. 10.1007/s10803-018-3515-z 29500756 PMC6041130 · DOI
  17. Hamilton CJ, Mammarella IC, & Giofre D (2018). Autisticlike traits in children are associated with enhanced performance in a qualitative visual working memory task. Autism Research, 11(11), 1494– 1499. 10.1002/aur.2028 30345714 · DOI
  18. Harrison P, & Oakland T (2003). Adaptive behavior assessment system, second edition, (Vol 22, pp. 367– 373). Torrance, CA: WPS.
  19. Happe F, Booth R, Charlton R, & Hughes C (2006). Executive function deficits in autism spectrum disorders and attention-deficit/hyperactivity disorder: Examining profiles across domains and ages. Brain and Cognition, 61(1), 25– 39. 10.1016/j.bandc.2006.03.004 16682102 · DOI · Paper page
  20. Hill EL (2004). Executive dysfunction in autism. Trends in Cognitive Sciences, 8(1), 26– 32. 14697400
  21. Hogeveen J, Krug MK, Elliott MV, Carter CS, & Solomon M (2018). Proactive control as a double-edged sword in autism spectrum disorder. Journal of Abnormal Psychology, 127(4), 429– 435. 10.1037/abn0000345 29745707 PMC5951414 · DOI
  22. Holm S (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6(2), 65– 70.
  23. Kirk HE, Gray KM, Ellis K, Taffe J, & Cornish KM (2016). Computerised attention training for children with intellectual and developmental disabilities: A randomised controlled trial. Journal of Child Psychology and Psychiatry, 57(12), 1380– 1389. 10.1111/jcpp.12615 27550746 · DOI
  24. Kouklari EC, Tsermentseli S, & Monks CP (2018). Hot and cool executive function in children and adolescents with autism spectrum disorder: Cross-sectional developmental trajectories. Child Neuropsychology, 24(8), 1088– 1114. 10.1080/09297049.2017.1391190 29052463 · DOI
  25. Krug MK, Elliott MV, Gordon AJ, Hogeveen J, Solomon M, Elliott MV, … Solomon M (2020). Proactive control in adolescents and young adults with autism spectrum disorder: Unimpaired but associated with symptoms of depression. Journal of Abnormal Psychology, 129, 517– 527. 32406696 PMC7473487
  26. Liss M, Fein D, Allen D, Dunn M, Feinstein C, Morris R, … Rapin I (2001). Executive functioning in high-functioning children with autism. Journal of Child Psychology and Psychiatry, 42(2), 261– 270. 11280422
  27. Lo YT, Mendell NR, & Rubin DB (2001). Testing the number of components in a normal mixture. Biometrika, 88(3), 767– 778. 10.1093/biomet/88.3.767 · DOI · Paper page
  28. Lord C, Risi S, Lambrecht L, Cook EH Jr., Leventhal BL, DiLavore PC, … Rutter M (2000). The autism diagnostic observation schedule-generic: A standard measure of social and communication deficits associated with the spectrum of autism. Journal of Autism and Developmental Disorders, 30 (3), 205– 223. 11055457
  29. Luna B (2009). Developmental changes in cognitive control through adolescence. Advances in Child Development and Behavior, 37, 233– 278. 19673164 PMC2782527
  30. Luna B, Doll SK, Hegedus SJ, Minshew NJ, & Sweeney JA (2007). Maturation of executive function in autism. Biological Psychiatry, 61(4), 474– 481. 10.1016/j.biopsych.2006.02.030 16650833 · DOI · Paper page
  31. Maister L, Simons JS, & Plaisted-Grant K (2013). Executive functions are employed to process episodic and relational memories in children with autism spectrum disorders. Neuropsychology, 27(6), 615– 627. 10.1037/a0034492 24245930 PMC3907063 · DOI
  32. Miller EK, & Cohen JD (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24, 167– 202. 10.1146/annurev.neuro.24.1.167 11283309 · DOI · Paper page
  33. Miller GA, & Chapman JP (2001). Misunderstanding analysis of covariance. Journal of Abnormal Psychology, 110(1), 40– 48. 10.1037//0021-843x.110.1.40 11261398 · DOI · Paper page
  34. Norbury CF, Griffiths H, & Nation K (2010). Sound before meaning: Word learning in autistic disorders. Neuropsychologia, 48 (14), 4012– 4019. 10.1016/j.neuropsychologia.2010.10.015 20951710 · DOI
  35. Nylund KL, Asparouhov T, & Muthen BO (2008). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling: A Multidisciplinary Journal, 15(1), 182– 182. 10.1080/10705510701793320 · DOI
  36. Ozonoff S, & Strayer DL (2001). Further evidence of intact working memory in autism. Journal of Autism and Developmental Disorders, 31(3), 257– 263. 11518480
  37. Pellicano E (2012). The development of executive function in autism. Autism Research and Treatment, 2012, 146132. 10.1155/2012/146132 PMC3420556 22934168 · DOI
  38. Pennington BF, & Ozonoff S (1996). Executive functions and developmental psychopathology. Journal of Child Psychology and Psychiatry, 37(1), 51– 87. 8655658
  39. Poljac E, Hoofs V, Princen MM, & Poljac E (2017). Understanding behavioural rigidity in autism spectrum conditions: The role of intentional control. Journal of Autism and Developmental Disorders, 47(3), 714– 727. 10.1007/s10803-016-3010-3 28070785 · DOI
  40. Rommelse NN, Geurts HM, Franke B, Buitelaar JK, & Hartman CA (2011). A review on cognitive and brain endo-phenotypes that may be common in autism spectrum disorder and attention-deficit/hyperactivity disorder and facilitate the search for pleiotropic genes. Neuroscience and Biobehavioral Reviews, 35(6), 1363– 1396. 21382410
  41. Rosenthal M, Wallace GL, Lawson R, Wills MC, Dixon E, Yerys BE, & Kenworthy L (2013). Impairments in real-world executive function increase from childhood to adolescence in autism spectrum disorders. Neuropsychology, 27(1), 13– 18. 10.1037/a0031299 23356593 PMC4747021 · DOI · Paper page
  42. Russell J, Jarrold C, & Henry L (1996). Working memory in children with autism and with moderate learning difficulties. Journal of Child Psychology and Psychiatry, 37(6), 673– 686. 8894948
  43. Samson F, Mottron L, Soulieres I, & Zeffiro TA (2012). Enhanced visual functioning in autism: An ALE meta-analysis. Human Brain Mapping, 33(7), 1553– 1581. 10.1002/hbm.21307 21465627 PMC6870295 · DOI · Paper page
  44. Schmitt LM, White SP, Cook EH, Sweeney JA, & Mosconi MW (2018). Cognitive mechanisms of inhibitory control deficits in autism spectrum disorder. Journal of Child Psychology and Psychiatry, 59(5), 586– 595. 10.1111/jcpp.12837 29052841 PMC5906199 · DOI
  45. Solomon M, Hogeveen J, Libero L, & Nordahl C (2017). An altered scaffold for information processing: Cognitive control development in adolescents with autism. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2(6), 464– 475. 10.1016/j.bpsc. 2017.06.002 PMC5600519 28924621 · DOI
  46. Solomon M, McCauley JB, Iosif AM, Carter CS, & Ragland JD (2016). Cognitive control and episodic memory in adolescents with autism spectrum disorders. Neuropsychologia, 89, 31– 41. 10.1016/j.neuropsychologia.2016.05.013 27184119 PMC5521263 · DOI
  47. Solomon M, Ozonoff SJ, Cummings N, & Carter CS (2008). Cognitive control in autism spectrum disorders. International Journal of Developmental Neuroscience, 26(2), 239– 247. 10.1016/j.ijdevneu.2007.11.001 18093787 PMC2695998 · DOI · Paper page
  48. Solomon M, Ozonoff SJ, Ursu S, Ravizza S, Cummings N, Ly S, & Carter CS (2009). The neural substrates of cognitive control deficits in autism spectrum disorders. Neuropsychologia, 47(12), 2515– 2526. 10.1016/j.neuropsychologia.2009.04.019 19410583 PMC2766616 · DOI · Paper page
  49. Solomon M, Ragland JD, Niendam TA, Lesh TA, Beck JS, Matter JC, … Carter CS (2015). Atypical learning in autism spectrum disorders: A functional magnetic resonance imaging study of transitive inference. Journal of the American Academy of Child and Adolescent Psychiatry, 54, 947– 955. 26506585 PMC4624100
  50. Soulieres I, Dawson M, Samson F, Barbeau EB, Sahyoun CP, Strangman GE, … Mottron L (2009). Enhanced visual processing contributes to matrix reasoning in autism. Human Brain Mapping, 30(12), 4082– 4107. 10.1002/hbm.20831 19530215 PMC2787806 · DOI
  51. Steiner NJ, Sheldrick RC, Gotthelf D, & Perrin EC (2011). Computer-based attention training in the schools for children with attention deficit/hyperactivity disorder: A preliminary trial. Clinical Pediatrics (Phila), 50(7), 615– 622. 10.1177/0009922810397887 21561933 · DOI · Paper page
  52. Tamm L, Epstein JN, Peugh JL, Nakonezny PA, & Hughes CW (2013). Preliminary data suggesting the efficacy of attention training for school-aged children with ADHD. Developmental Cognitive Neuroscience, 4, 16– 28. 10.1016/j.dcn.2012.11.004 23219490 PMC3617931 · DOI
  53. Thomas MS, Annaz D, Ansari D, Scerif G, Jarrold C, & Karmiloff-Smith A (2009). Using developmental trajectories to understand developmental disorders. Journal of Speech, Language, and Hearing Research, 52(2), 336– 358. 10.1044/1092-4388(2009/07-0144) 19252129 · DOI
  54. Tulsky DS, Carlozzi N, Chiaravalloti ND, Beaumont JL, Kisala PA, Mungas D, … Gershon R (2014). NIH Toolbox Cognition Battery (NIHTB-CB): List sorting test to measure working memory. Journal of the International Neuropsychological Society, 20(6), 599– 610. 10.1017/S135561771400040X 24959983 PMC4426848 · DOI · Paper page
  55. Wang Y, Zhang YB, Liu LL, Cui JF, Wang J, Shum DH, … Chan RC (2017). A meta-analysis of working memory impairments in autism spectrum disorders. Neuropsychology Review, 27(1), 46– 61. 10.1007/s11065-016-9336-y 28102493 · DOI · Paper page
  56. Wechsler D (2011). Wechsler Abbreviated Scale of Intelligence - Second Edition: Manual. San Antonio, TX: Pearson.
  57. Zelazo PD (2006). The Dimensional Change Card Sort (DCCS): A method of assessing executive function in children. Nature Protocols, 1(1), 297– 301. 10.1038/nprot.2006.46 17406248 · DOI · Paper page

Authors
Solomon, M., Gordon, A., Iosif, A., Geddert, R., Krug, M. K., Mundy, P., & Hessl, D.
Affiliations
  • University of California, Davis (US)
  • Duke University (US)
Corresponding author
Solomon, Marjorie
Venue
Autism Research
Publisher
Wiley
Published
2020-10-02
Volume
14
Issue
3
Pages
500-511
ISSN
  • 1939-3792 (ISSN-L)
  • 1939-3806
OpenAlex
W3090287073
Cited by
20
References
71
Citations by year
2026: 1 · 2025: 9 · 2024: 1 · 2023: 4 · 2022: 3 · 2021: 2
FWCI
1.21
Type
journal article
Language
en
Open access
Locations
  • Autism Research (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (P50 HD103526, R01 HD076189)
  • National Institute of Mental Health (R01 MH103284, R01 MH106518)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
  • Social Sciences › Psychology › Neuropsychology and Physiological Psychology › Developmental and Educational Neuropsychology
  • Social Sciences › Psychology › Developmental and Educational Psychology › Child and Animal Learning Development
Keywords
autism spectrum disorder, adolescents and young adults, NIH Toolbox Cognition Battery, fluid intelligence, crystallized intelligence, executive dysfunction, inhibitory control, cognitive flexibility, episodic memory, processing speed, cognitive development, cognitive profile, adaptive behavior, attention deficits, age differences in cognition, cognitive aging, typical development
MeSH terms
Autism Spectrum Disorder, Adolescent, Attention Deficit Disorder with Hyperactivity, Child, Cognition, Cross-Sectional Studies, Female, Humans, Intelligence Tests, Male, Neuropsychological Tests, Young Adult

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