Brain development of a school-aged boy with autism spectrum condition talented in arithmetic: a case report

Abstract

Whereas autism spectrum condition is known for its social and communicative challenges, some autistic children demonstrate unusual islets of abilities including those related to mathematics, the neurobiological underpinnings of which are increasingly becoming the focus of research. Here we describe an 8-year-old autistic boy with intellectual and language challenges, yet exceptional arithmetic ability. He can perform verbal-based multiplication of three- and even four-digit numbers within 20 seconds. To gain insights into the neural basis of his talent, we investigated the gray matter in the child's brain in comparison to typical development, applying voxel-based morphometry to magnetic resonance imaging data. The case exhibited reduced gray matter volume in regions associated with arithmetic, which may suggest an accelerated development of brain regions with arithmetic compared to typically developing individuals: potentially a key factor contributing to his exceptional talent. Taken together, this case report describes an example of the neurodiversity of autism. Our research provides valuable insights into the potential neural basis of exceptional arithmetic abilities in individuals with the autism spectrum and its potential contribution to depicting the diversity and complexity of autism.

Keywords

Autism spectrum condition / arithmetic talent / gray matter / voxel-based morphometry / magnetic resonance imaging / case report

Supplementary data

Supplementary data is available at Psychoradiology Journal online.

Author contributions

Weixing Zhao (Conceptualization, Software, Visualization, Writing - original draft), Lei Li (Investigation, Methodology, Software), Xiujie Yang (Resources, Writing - review & editing), Xiaotian Wang (Investigation, Software), Juan Kou (Supervision), Jia Che (Investigation, Resources), Huafu Chen (Funding acquisition, Supervision), Qi Wang (Investigation, Resources, Supervision), and Xujun Duan (Conceptualization, Funding acquisition, Supervision, Writing - review & editing)

Conflict of interest

The authors declare to not have any conflicts of interest.

Acknowledgement

This study was supported by the National Natural Science Foundation of China (62273076, 82121003, and 62036003), Fundamental Research Funds for Central Universities (ZYGX2019Z017), and National Social Science Foundation of China (20&ZD296). We also gratefully acknowledge the child and his family for participating in the research.

Ethics approval and consent to participate

Ethical approval was obtained from the local Institutional Review Boards, and written informed consent was obtained from the parents of the underage participants in this study.

References

[1] American Psychiatric Association (2013) Diagnostic and Statistical Manual of Mental Disorders: DSM-5, Vol. 5: Washington, DC: American Psychiatric Association.

[2] Ashburner J, Friston KJ (2000) Voxel-based morphometry-the methods. Neuroimage 11:805-21.

[3] Baron-Cohen S, Ashwin E, Ashwin C, et al. (2009) Talent in autism: hyper-systemizing, hyper-attention to detail and sensory hypersensitivity. Phil Trans R Soc B 364:1377-83.

[4] Baron-Cohen S, Lombardo MV (2022) Autism and talent: the cognitive and neural basis of systemizing. Dialog Clin Neurosci 9:343-53.

[5] Bodfish JW, Symons FJ, Parker DE, et al., (1999) The Repetitive Behavior Scales: A test manual. Morganton, NC: Western Carolina Center Research Reports.

[6] Constantino JN, Davis SA, Todd RD, et al. (2003) Validation of a brief quantitative measure of autistic traits: comparison of the social responsiveness scale with the autism diagnostic interviewrevised. J Autism Dev Disord 33:427-33.

[7] Deringer VL, Bartók AP, Bernstein N, et al. (2021) Gaussian process regression for materials and molecules. Chem Rev 121:10073-141.

[8] Han Z, Davis N, Fuchs L, et al. (2013) Relation between brain architecture and mathematical ability in children: a DBM study. Magn Reson Imaging 31:1645-56.

[9] Happé F, Frith U (2006) The weak coherence account: detail-focused cognitive style in autism spectrum disorders. J Autism Dev Disord 36:5-25.

[10] Kamp-Becker I, Albertowski K, Becker J, et al. (2018) Diagnostic accuracy of the ADOS and ADOS-2 in clinical practice. Eur Child Adolesc Psychiatry 27:1193-207.

[11] Li Y, Hu Y, Wang Y, et al. (2013) Individual structural differences in left inferior parietal area are associated with schoolchildrens' arithmetic scores. Front Hum Neurosci 7:844.

[12] Lord C, Rutter M, Dilavore P, et al. (2012) Autism Diagnostic Observation Schedule, 2nd ed (ADOS-2). Los Angeles, CA: Western Psychological Corporation.

[13] Miller LK (1999) The savant syndrome: intellectual impairment and exceptional skill. Psychol Bull 125:31.

[14] Mills KL, Lalonde F, Clasen LS, et al. (2014) Developmental changes in the structure of the social brain in late childhood and adolescence. Soc Cognit Affect Neurosci 9:123-31.

[15] Mottron L, Dawson M, Soulières I, et al. (2006) Enhanced perceptual functioning in autism: an update, and eight principles of autistic perception. J Autism Dev Disord 36:27-43.

[16] Mottron L, Dawson M, Soulières I (2009) Enhanced perception in savant syndrome: patterns, structure and creativity. Phil Trans R Soc B 364:1385-91.

[17] Munson J, Dawson G, Sterling L, et al. (2008) Evidence for latent classes of IQ in young children with autism spectrum disorder. Am J Ment Retard 113:439-52.

[18] Narvacan K, Treit S, Camicioli R, et al. (2017) Evolution of deep gray matter volume across the human lifespan. Hum Brain Mapp 38:3771-90.

[19] Peters L, De Smedt B (2018) Arithmetic in the developing brain: a review of brain imaging studies. Dev Cogn Neurosci 30: 265-79.

[20] Price GR, Wilkey ED, Yeo DJ, et al. (2016) The relation between 1st grade grey matter volume and 2nd grade math competence. Neuroimage 124:232-7.

[21] Ranpura A, Isaacs E, Edmonds C, et al. (2013) Developmental trajectories of grey and white matter in dyscalculia. Trends Neurosci Educ 2:56-64.

[22] Raven J (2003) Raven progressive matrices. In: Handbook of Nonverbal Assessment. Boston, MA: Springer, 223-37.

[23] Rellini E, Tortolani D, Trillo S, et al. (2004) Childhood Autism Rating Scale (CARS) and Autism Behavior Checklist (ABC) correspondence and conflicts with DSM-IV criteria in diagnosis of autism. J Autism Dev Disord 34:703-8.

[24] Rotzer S, Kucian K, Martin E, et al. (2008) Optimized voxel-based morphometry in children with developmental dyscalculia. Neuroimage 39:417-22.

[25] Rutter M, Le Couteur A, Lord C (2003) Autism Diagnostic InterviewRevised, Vol. 29. Los Angeles, CA, USA: Western Psychological Services, 30.

[26] Rykhlevskaia E (2009) Neuroanatomical correlates of developmental dyscalculia: combined evidence from morphometry and tractography. Front Hum Neurosci. 3:1014.

[27] Schopler E, Lansing MD, Reichler RJ, et al. (2005) Psycho-educational profile: TEACCH individualized psycho-educational assessment for children with autism spectrum disorders (3rd Ed) (PEP-3). Austin, TX: Pro-Ed.

[28] Tzourio-Mazoyer N, Landeau B, Papathanassiou D, et al. (2002) Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15:273-89.

[29] Volkmar FR, Cicchetti DV, Dykens E, et al. (1988) An evaluation of the autism behavior checklist. J Autism Dev Disord 18:81-97.

[30] Wendling BJ (2014) Woodcock-Johnson IV Tests of Achievement:Examiner Training Workbook. Itasca, Illinois: Riverside Publishing Company.