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Advances in MRI brain networks in children with intellectual disabilities
MU Fangfang  MA Xuejin  JIANG Lin  LI Shiguang 

Cite this article as: MU F F, MA X J, JIANG L, et al. Advances in MRI brain networks in children with intellectual disabilities[J]. Chin J Magn Reson Imaging, 2023, 14(12): 116-120. DOI:10.12015/issn.1674-8034.2023.12.020.


[Abstract] Intellectual disability (ID) is a neurodevelopmental disorder, characterized by intellectual and adaptive dysfunction. It has a high incidence and affects patients for lifelong, causing a huge burden on patients, their families and society. The pathogenesis of ID is unclear, thus there still haven't an effective prevention and treatment measures. Moreover, the study of pathogenesis of ID seriously limited by the diverse pathogenic factors. In recent years, the prevalent application of MRI brain network research in neuropsychiatric diseases provides a new perspective for the study of the pathogenesis of ID. This article reviews the research findings on MRI brain network in children with ID in the past ten years, and explores the possible common characteristics and application prospects of brain network changes in children with ID for such disorders, in order to provide neuroimaging evidence for the study of the pathogenesis of children with ID.
[Keywords] intellectual disability；children；magnetic resonance imaging；brain network

MU Fangfang   MA Xuejin   JIANG Lin   LI Shiguang*  

Department of Radiology, the Third Affiliated Hospital of Zunyi Medical University (the First People's Hospital of Zunyi), Zunyi 563099, China

Corresponding author: LI S G, E-mail: imaging_sgli@163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Science and Technology Plan Project of Guizhou Province [No. Qian Ke He Foundation-ZK (2022) General 582]; Special Fund Project for Science and Technology Cooperation of Guizhou Province [No. Sheng Shi Ke He (2015) 54]; Innovative Talent Team Training Project of Zunyi City [No. Zun Shi Ren Cai (2020) 6].
Received  2023-09-17
Accepted  2023-11-07
DOI: 10.12015/issn.1674-8034.2023.12.020
Cite this article as: MU F F, MA X J, JIANG L, et al. Advances in MRI brain networks in children with intellectual disabilities[J]. Chin J Magn Reson Imaging, 2023, 14(12): 116-120. DOI:10.12015/issn.1674-8034.2023.12.020.

[1]
ASSOCIATION A P. Diagnostic and Statistical Manual of Mental Disorders[M]. Arlington: VA, 2013.
[2]
JI G. Bulletin on Key Data of the Second National Sample Survey of Persons with Disabilities (No. 2)[J]. Disability in China, 2007, (6): 12-13.
[3]
SYDNOR V J, LARSEN B, SEIDLITZ J, et al. Intrinsic activity development unfolds along a sensorimotor-association cortical axis in youth[J]. Nat Neurosci, 2023, 26(4): 638-649. DOI: 10.1038/s41593-023-01282-y.
[4]
ROMANO C. Genetics and clinical neuroscience in intellectual disability[J/OL]. Brain Sci, 2022, 12(3): 338 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8946658/. DOI: 10.3390/brainsci12030338.
[5]
MAIA N, NABAIS SÁ M J, MELO-PIRES M, et al. Intellectual disability genomics: current state, pitfalls and future challenges[J/OL]. BMC Genomics, 2021, 22(1): 909 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8686650/. DOI: 10.1186/s12864-021-08227-4.
[6]
HANLY C, SHAH H, AU P Y B, et al. Description of neurodevelopmental phenotypes associated with 10 genetic neurodevelopmental disorders: A scoping review[J]. Clin Genet, 2021, 99(3): 335-346. DOI: 10.1111/cge.13882.
[7]
WATKINS L V, LINEHAN C, BRANDT C, et al. Epilepsy in adults with neurodevelopmental disability - what every neurologist should know[J]. Epileptic Disord, 2022, 24(1): 9-25. DOI: 10.1684/epd.2021.1366.
[8]
FARAHANI F V, KARWOWSKI W, LIGHTHALL N R. Application of graph theory for identifying connectivity patterns in human brain networks: A systematic review[J/OL]. Front Neurosci, 2019, 13: 585 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6582769/. DOI: 10.3389/fnins.2019.00585.
[9]
LIN Q, SHI Y, HUANG H, et al. Functional brain network alterations in the co-occurrence of autism spectrum disorder and attention deficit hyperactivity disorder[J/OL]. Eur Child Adolesc Psychiatry, 2023, [2023-09-15]. https://link.springer.com/article/10.1007/s00787-023-02165-0. DOI: 10.1007/s00787-023-02165-0.
[10]
SOMAN S M, VIJAYAKUMAR N, THOMSON P, et al. Functional and structural brain network development in children with attention deficit hyperactivity disorder[J]. Hum Brain Mapp, 2023, 44(8): 3394-3409. DOI: 10.1002/hbm.26288.
[11]
BLUME J, DHANASEKARA C S, KAHATHUDUWA C N, et al. Central executive and default mode networks: An appraisal of executive function and social skill brain-behavior correlates in youth with autism spectrum disorder[J/OL]. J Autism Dev Disord, 2023 [2023-09-15]. https://link.springer.com/article/10.1007/s00787-023-02165-0. DOI: 10.1007/s10803-023-05961-4.
[12]
RASHIDI-RANJBAR N, RAJJI T K, HAWCO C, et al. Association of functional connectivity of the executive control network or default mode network with cognitive impairment in older adults with remitted major depressive disorder or mild cognitive impairment[J]. Neuropsychopharmacology, 2023, 48(3): 468-477. DOI: 10.1038/s41386-022-01308-2.
[13]
CURTIN P, NEUFELD J, CURTIN A, et al. Altered Periodic Dynamics in the Default Mode Network in Autism and Attention-Deficit/Hyperactivity Disorder[J]. Biol Psychiatry, 2022, 91(11): 956-966. DOI: 10.1016/j.biopsych.2022.01.010.
[14]
NAIR A, JOLLIFFE M, LOGRASSO Y S S, et al. A Review of Default Mode Network Connectivity and Its Association With Social Cognition in Adolescents With Autism Spectrum Disorder and Early-Onset Psychosis[J/OL]. Front Psychiatry, 2020, 11: 614 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330632/. DOI: 10.3389/fpsyt.2020.00614.
[15]
CARBÓ-CARRETÉ M, CAÑETE-MASSÉ C, FIGUEROA-JIMÉNEZ M D, et al. Relationship between quality of life and the complexity of default mode network in resting state functional magnetic resonance image in Down syndrome[J]. Int J Environ Res Public Health, 2020, 17(19): 7127 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7579576/. DOI: 10.3390/ijerph17197127.
[16]
FIGUEROA-JIMENEZ M D, CARBÓ-CARRETÉ M, CAÑETE-MASSÉ C, et al. Complexity analysis of the default mode network using resting-state fMRI in Down syndrome: Relationships highlighted by a neuropsychological assessment[J/OL]. Brain Sci, 2021, 11(3): 311 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8001398/. DOI: 10.3390/brainsci11030311.
[17]
DESERISY M, RAMPHAL B, PAGLIACCIO D, et al. Frontoparietal and default mode network connectivity varies with age and intelligence[J/OL]. Dev Cogn Neurosci, 2021, 48: 100928 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7848769/. DOI: 10.1016/j.dcn.2021.100928.
[18]
MA X, TAN J, JIANG L, et al. Aberrant structural and functional developmental trajectories in children with intellectual disability[J/OL]. Front Psychiatry, 2021, 12: 634170 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8076543/. DOI: 10.3389/fpsyt.2021.634170.
[19]
POWER J D, COHEN A L, NELSON S M, et al. Functional network organization of the human brain[J]. Neuron, 2011, 72(4): 665-678. DOI: 10.1016/j.neuron.2011.09.006.
[20]
JUNG R E, HAIER R J. The Parieto-frontal integration theory (P-FIT) of intelligence: converging neuroimaging evidence[J]. Behav Brain Sci, 2007, 30(2): 135-187. DOI: DOI:10.1017/S0140525X07001185.
[21]
DUNCAN J. The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour[J]. Trends Cogn Sci, 2010, 14(4): 172-179. DOI: 10.1016/j.tics.2010.01.004.
[22]
SCARIATI E, SCHAER M, KARAHANOGLU I, et al. Large-scale functional network reorganization in 22q11.2 deletion syndrome revealed by modularity analysis[J]. Cortex, 2016, 82: 86-99. DOI: 10.1016/j.cortex.2016.06.004.
[23]
CAÑETE-MASSÉ C, CARBÓ-CARRETÉ M, PERÓ-CEBOLLERO M, et al. Abnormal degree centrality and functional connectivity in Down syndrome: A resting-state fMRI study[J/OL]. Int J Clin Health Psychol, 2023, 23(1): 100341 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9551068/. DOI: 10.1016/j.ijchp.2022.100341.
[24]
DUNCAN J, ASSEM M, SHASHIDHARA S. Integrated intelligence from distributed brain activity[J]. Trends Cogn Sci, 2020, 24(10): 838-852. DOI: 10.1016/j.tics.2020.06.012.
[25]
ASSEM M, GLASSER M F, VAN ESSEN D C, et al. A domain-general cognitive core defined in multimodally parcellated human cortex[J]. Cereb Cortex, 2020, 30(8): 4361-4380. DOI: 10.1093/cercor/bhaa023.
[26]
DIACHEK E, BLANK I, SIEGELMAN M, et al. The domain-general multiple demand (MD) network does not support core aspects of language comprehension: A large-scale fMRI investigation[J]. J Neurosci, 2020, 40(23): 4536-4550. DOI: 10.1523/jneurosci.2036-19.2020.
[27]
WOOLGAR A, DUNCAN J, MANES F, et al. The multiple-demand system but not the language system supports fluid intelligence[J]. Nat Hum Behav, 2018, 2(3): 200-204. DOI: 10.1038/s41562-017-0282-3.
[28]
SMITH V, PINASCO C, ACHTERBERG J, et al. Fluid intelligence and naturalistic task impairments after focal brain lesions[J]. Cortex, 2022, 146: 106-115. DOI: 10.1016/j.cortex.2021.09.020.
[29]
IKUTA T, GOLLNICK H M, RUTLEDGE A N. Age associated decline in the arcuate fasciculus and IQ[J]. Brain Imaging Behav, 2020, 14(2): 362-367. DOI: 10.1007/s11682-019-00154-z.
[30]
SIMPSON-KENT I L, FUHRMANN D, BATHELT J, et al. Neurocognitive reorganization between crystallized intelligence, fluid intelligence and white matter microstructure in two age-heterogeneous developmental cohorts[J/OL]. Dev Cogn Neurosci, 2020, 41: 100743 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6983934/. DOI: 10.1016/j.dcn.2019.100743.
[31]
SUPRANO I, KOCEVAR G, STAMILE C, et al. White matter microarchitecture and structural network integrity correlate with children intelligence quotient[J/OL]. Sci Rep, 2020, 10(1): 20722 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7691327/. DOI: 10.1038/s41598-020-76528-x.
[32]
RAMLI N, YAP A, MURIDAN R, et al. Microstructural abnormalities found in uncinate fasciculus and superior cerebellar tracts in children with global developmental delay: a feasibility study[J/OL]. Clin Radiol, 2020, 75(1): 77.e15-77.e22 [2023-09-15]. https://linkinghub.elsevier.com/retrieve/pii/S0009-9260(19)30582-3. DOI: 10.1016/j.crad.2019.09.134.
[33]
TAKEGUCHI R, KURODA M, TANAKA R, et al. Structural and functional changes in the brains of patients with Rett syndrome: A multimodal MRI study[J/OL]. J Neurol Sci, 2022, 441: 120381 [2023-09-15]. https://linkinghub.elsevier.com/retrieve/pii/S0022-510X(22)00243-X. DOI: 10.1016/j.jns.2022.120381.
[34]
JEONG J W, SUNDARAM S, BEHEN M E, et al. Differentiation of speech delay and global developmental delay in children using DTI Tractography-based connectome[J]. AJNR Am J Neuroradiol, 2016, 37(6): 1170-1177. DOI: 10.3174/ajnr.A4662.
[35]
ZHAN L, JENKINS L M, ZHANG A, et al. Baseline connectome modular abnormalities in the childhood phase of a longitudinal study on individuals with chromosome 22q11.2 deletion syndrome[J]. Hum Brain Mapp, 2018, 39(1): 232-248. DOI: 10.1002/hbm.23838.
[36]
BATHELT J, BARNES J, RAYMOND F L, et al. Global and local connectivity differences converge with gene expression in a neurodevelopmental disorder of known genetic origin[J]. Cereb Cortex, 2017, 27(7): 3806-3817. DOI: 10.1093/cercor/bhx027.
[37]
WANG J, WANG Z, ZHANG H, et al. White matter structural and network topological changes underlying the behavioral phenotype of MECP2 mutant monkeys[J]. Cereb Cortex, 2021, 31(12): 5396-5410. DOI: 10.1093/cercor/bhab166.
[38]
KONG Y, LI Q B, YUAN Z H, et al. Multimodal neuroimaging in Rett syndrome with MECP2 mutation[J/OL]. Front Neurol, 2022, 13: 838206 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8904872/. DOI: 10.3389/fneur.2022.838206.
[39]
OYEFIADE A, MOXON-EMRE I, BEERA K, et al. Structural connectivity and intelligence in brain-injured children[J/OL]. Neuropsychologia, 2022, 173: 108285 [2023-09-15]. https://linkinghub.elsevier.com/retrieve/pii/S0028-3932(22)00144-0. DOI: 10.1016/j.neuropsychologia.2022.108285.
[40]
ESTRADA E, FERRER E, ROMÁN F J, et al. Time-lagged associations between cognitive and cortical development from childhood to early adulthood[J]. Dev Psychol, 2019, 55(6): 1338-1352. DOI: 10.1037/dev0000716.
[41]
VIJAYAKUMAR N, BALL G, SEAL M L, et al. The development of structural covariance networks during the transition from childhood to adolescence[J/OL]. Sci Rep, 2021, 11(1): 9451 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097025/. DOI: 10.1038/s41598-021-88918-w.
[42]
SOLÉ-CASALS J, SERRA-GRABULOSA J M, ROMERO-GARCIA R, et al. Structural brain network of gifted children has a more integrated and versatile topology[J]. Brain Struct Funct, 2019, 224(7): 2373-2383. DOI: 10.1007/s00429-019-01914-9.
[43]
WOODBURN M, BRICKEN C L, WU Z, et al. The maturation and cognitive relevance of structural brain network organization from early infancy to childhood[J/OL]. Neuroimage, 2021, 238: 118232 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8372198/. DOI: 10.1016/j.neuroimage.2021.118232.
[44]
KING D J, SERI S, CATROPPA C, et al. Structural-covariance networks identify topology-based cortical-thickness changes in children with persistent executive function impairments after traumatic brain injury[J/OL]. Neuroimage, 2021, 244: 118612 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8591373/. DOI: 10.1016/j.neuroimage.2021.118612.
[45]
BRUNO J L, HOSSEINI S M H, SAGGAR M, et al. Altered brain network segregation in fragile X syndrome revealed by structural connectomics[J]. Cereb Cortex, 2017, 27(3): 2249-2259. DOI: 10.1093/cercor/bhw055.
[46]
SANDINI C, ZÖLLER D, SCARIATI E, et al. Development of structural covariance from childhood to adolescence: A longitudinal study in 22q11.2DS[J/OL]. Front Neurosci, 2018, 12: 327 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5968113/. DOI: 10.3389/fnins.2018.00327.
[47]
EVERAERT E, VORSTMAN J A S, SELTEN I S, et al. Executive functioning in preschoolers with 22q11.2 deletion syndrome and the impact of congenital heart defects[J/OL]. J Neurodev Disord, 2023, 15(1): 15 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181926/. DOI: 10.1186/s11689-023-09484-y.
[48]
SCHETTINI E, HIERSCHE K J, SAYGIN Z M. Individual variability in performance reflects selectivity of the multiple demand network among children and adults[J]. J Neurosci, 2023, 43(11): 1940-1951. DOI: 10.1523/jneurosci.1460-22.2023.
[49]
FISKE A, HOLMBOE K. Neural substrates of early executive function development[J]. Dev Rev, 2019, 52: 42-62. DOI: 10.1016/j.dr.2019.100866.
[50]
SCHMITT L M, SHAFFER R C, HESSL D, et al. Executive function in fragile X syndrome: A systematic review[J/OL]. Brain Sci, 2019, 9(1): 15 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6356760/. DOI: 10.3390/brainsci9010015.
[51]
SUN H M, LI Q Y, XIAO R Y, et al. A structural MRI study of global developmental delay in infants (＜2 years old)[J/OL]. Front Neurol, 2022, 13: 952405 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9434372/. DOI: 10.3389/fneur.2022.952405.
[52]
GUPTA C, CHANDRASHEKAR P, JIN T, et al. Bringing machine learning to research on intellectual and developmental disabilities: taking inspiration from neurological diseases[J/OL]. J Neurodev Disord, 2022, 14(1): 28 [2023-09-15]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9059371/. DOI: 10.1186/s11689-022-09438-w.
[53]
BARBEY A K. Network neuroscience theory of human intelligence[J]. Trends Cogn Sci, 2018, 22(1): 8-20. DOI: 10.1016/j.tics.2017.10.001.

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