Top

Journal of Autism and Developmental Disorders

Gepubliceerd in:

04-05-2023 | Original Paper

Eigenvector Centrality Characterization on fMRI Data: Gender and Node Differences in Normal and ASD Subjects

Author name

Auteur: Papri Saha

Gepubliceerd in: Journal of Autism and Developmental Disorders | Uitgave 7/2024

Abstract

With the budding interests of structural and functional network characteristics as potential parameters for abnormal brains, an essential and thus simpler representation and evaluations have become necessary. Eigenvector centrality measure of functional magnetic resonance imaging (fMRI) offer region wise network representations through fMRI diagnostic maps. The article investigates the suitability of network node centrality values to discriminate ASD subject groups compared to typically developing controls following a boxplot formalism and a classification and regression tree model. Region wise differences between normal and ASD subjects primarily belong to the frontoparietal, limbic, ventral attention, default mode and visual networks. The reduced number of regions-of-interests (ROI) clearly suggests the benefit of automated supervised machine learning algorithm over the manual classification method.

vorige artikel Parent-Child Interactions May Help to Explain Relations Between Parent Characteristics and Clinically Observed Child Autistic Behaviours

volgende artikel Brief report: bidirectional association of core autism features and cognitive abilities in early childhood

Achard, S., Salvador, R., Whitcher, B., Suckling, J., & Bullmore, E. (2006). A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. Journal Of Neuroscience, 26(1), 63–72.CrossRefPubMed

American Psychiatric Association. (2013). Diagnostic and statistical Manual of Mental Disorders. fifth ed Dsm-5. Washington, DC: American Psychiatric Press. https://doi.org/10.1176/appi.books.9780890425596.CrossRef

Andrews, D. S., et al. (2019). A diffusion-weighted imaging tract-based spatial statistics study of autism spectrum disorder in preschool-aged children. J Neurodev Disord, 11, 32.CrossRefPubMedPubMedCentral

Binnewijzend, M. A. A., Adriaanse, S. M., Van der Flier, W. M., Teunissen, C. E., de Munck, J. C., Stam, C. J., et al. (2014). Brain network alterations in Alzheimer’s disease measured by Eigenvector centrality in fMRI are related to cognition and CSF biomarkers. Human Brain Mapping, 35, 2383–2393. https://doi.org/10.1002/hbm.22335.CrossRefPubMed

Bonacich, P. (2007). Some unique properties of eigenvector centrality. Social Networks, 29, 555–564.CrossRef

Blum, K., & Chen, A. (2008). Attention-deficit-hyperactivity disorder and reward deficiency syndrome. Neuropsychiatric Disease And Treatment, 4, 893–918.PubMedPubMedCentral

Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1983). Classification and regression trees. Belmont, Ca: Wadsworth.

Bullmore, E., & Sporns, O. (2009). Complex brain networks: graph theoretical analysis of structural and functional systems. Neuroscience, 10, 186–198. https://doi.org/10.1038/nrn2575.CrossRefPubMed

Clark, L. A., & Pregibon, D. (1992). Tree-based models. In J.M. Chambers and T.J. Hastie, editors, Statistical Models in S, Wadsworth and Brooks/Cole, Pacific Grove, Ca.

Costa, L. F., Oliveira, O. N., Travieso, G., Ro- drogues, F. A., Boas, P. R. V., Antiqueira, L., Viana, M. P., & Rocha, L. E. C. (2011). Analyzing and modeling real-world phenomena with complex networks: a survey of applications. Advances in Physics, 60(3), 329–412.CrossRef

Courchesne, E. (2002). Abnormal early brain development in autism. Mol Psychiatry. 7(Suppl 2), S21–S23.

Davey, J., Thompson, H. E., Hallam, G., Karapanagiotidis, T., Murphy, C., Caso, I. D., Krieger-Redwood, K., Bernhardt, B. C., Smallwood, J., & Jefferies, E. (2016). Exploring the role of the posterior middle temporal gyrus in semantic cognition: integration of anterior temporal lobe with executive processes. Neuroimage, 137, 165–177. https://doi.org/10.1016/j.neuroimage.2016.05.051.CrossRefPubMed

Donges, J. F., Zou, Y., Marwan, N., & Kurths, J. (2009). The backbone of the climate network. Europhysics Letters, 87(4), 48007.CrossRef

dos santos Siqueira, A., Biazoli Junior, C. E., Comfort, W. E., Rohde, L. A., & Sato, J. R. (2014). Abnormal functional resting-state networks in ADHD: graph theory and pattern recognition analysis of fMRI data. Biomed Research International, 2014, 1–10. https://doi.org/10.1155/2014/380531.CrossRef

Ecker, C., Bookheimer, S. Y., & Murphy, D. G. (2015). Neuroimaging in autism spectrum disorder: brain structure and function across the lifespan. Lancet Neurology, 14, 1121–1134.CrossRefPubMed

Ezzati, A., Katz, M. J., Zammit, A. R., Lipton, M. L., Zimmerman, M. E., Sliwinski, M. J., & Lipton, R. B. (2016). Differential association of left and right hippocampal volumes with verbal episodic and spatial memory in older adults. Neuropsychologia, 93, 380–385. https://doi.org/10.1016/j.neuropsychologia.2016.08.016.CrossRefPubMedPubMedCentral

Fagiolo, G., Reyes, J., & Schiavo, S. (2009). World-trade web: topological properties, dynamics, and evolution. Physical Review E, 79(3), 036115.CrossRef

Findley, S. (2003). Age limits and adolescents. Paediatrics & Child Health, 8, 577–578.CrossRef

Gadad, B. S., Hewitson, L., Young, K. A., & German, D. C. (2013). Neuropathology and animal models of autism: genetic and environmental factors. Autism Res Treat. 2013, 731935.

Goldberg, M. C., Mostofsky, S. H., Cutting, L. E., Mahone, E. M., Astor, B. C., Denckla, M. B., et al. (2005). Subtle executive impairment in children with autism and children with ADHD. Journal of Autism and Developmental Disorders, 35, 279–293.CrossRefPubMed

Gong, G., He, Y., & Evans, A. C. (2011). Brain connectivity: gender makes a difference. The Neuroscientist : A Review Journal Bringing Neurobiology, Neurology And Psychiatry, 17, 575–591. https://doi.org/10.1177/1073858410386492.CrossRefPubMed

Grobelny, B. T., London, D., Hill, T. C., & North, E. (2018). Betweenness Centrality of Intracranial Electroencephalography Networks and Surgical Epilepsy Outcome. Clinical Neurophysiology, 129, https://doi.org/10.1016/j.clinph.2018.02.135.

Guimera, R., Mossa, S., Turtschi, A., & Amaral, L. N. (2005). The worldwide air transportation network: Anomalous centrality, community structure, and cities’ global roles. Proceedings of the National Academy of Sciences. 102(22), 7794–7799.

Horwitz, B., Rumsey, J. M., Grady, C. L., & Rapoport, S. I. (1988). The cerebral metabolic landscape in autism. Intercorrelations of regional glucose utilization. Archives Of Neurology, 45, 749–755.CrossRefPubMed

Kana, R. K., Keller, T. A., Cherkassky, V. L., Minshew, N. J., & Just, M. A. (2006). Sentence comprehension in autism: thinking in pictures with decreased functional connectivity. Brain, 129, 2484–2493.CrossRefPubMed

Lange, N., Travers, B. G., Bigler, E. D., Prigge, M. B., Froehlich, A. L., Nielsen, J. A., Cariello, A. N., Zielinski, B. A., Anderson, J. S., Fletcher, P. T., Alexander, A. A., & Lainhart, J. E. (2015). Longitudinal volumetric brain changes in autism spectrum disorder ages 6–35 years. Autism Research, 8, 82–93.CrossRefPubMed

Lee, J. K., et al. (2020). ). Sex differences in the amygdala resting-state connectome of children with Autism Spectrum Disorder. Biol Psychiatry Cogn Neurosci Neuroimaging, 5, 320–329.PubMed

Leirbakk, M. J. (2015). ADHD with co-occurring depression/anxiety in children: the relationship with somatic complaints and parental socio-economic position. J Psychol Abnorm Child, 4, 1–6. https://doi.org/10.4172/2329-9525.1000137.CrossRef

Libero, L. E., DeRamus, T. P., Deshpande, H. D., & Kana, R. K. (2014). Surface-based morphometry of the cortical architecture of autism spectrum disorders: volume, thickness, area, and gyrification. Neuropsychologia, 62, 1–10.CrossRefPubMed

Lohmann, G., Margulies, D. S., Horstmann, A., Pleger, B., Lepsien, J., Goldhahn, D., et al. (2010). Eigenvector centrality mapping for analyzing connectivity patterns in FMRI data of the human brain. PLoS One, 5, e10232. https://doi.org/10.1371/journal.pone.0010232.CrossRefPubMedPubMedCentral

Lorberboym, M., Watemberg, N., Nissenkorn, A., Nir, B., & Lerman-Sagie, T. (2004). Technetium 99m ethylcysteinate dimer single-photon emission computed tomography (SPECT) during intellectual stress test in children and adolescents with pure. Journal Of Child Neurology, 19, 91–96.CrossRefPubMed

Maximo, J. O., Cadena, E. J., & Kana, R. K. (2014). The implications of brain connectivity in the neuropsychology of autism. Neuropsychology Review, 24, 16–31.CrossRefPubMedPubMedCentral

Power, J. D., et al. (2011). Functional network organization of the human brain. Neuron, 72(4), 665–678.CrossRefPubMedPubMedCentral

Raileanu, L. E., & Stoffel, K. (2004). Theoretical comparison between the Gini Index and Information Gain Criteria. Annals of Mathematics and Artificial Intelligence, 41(1), 77–93.CrossRef

Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52, 1059–1069. doi:https://doi.org/10.1016/j.neuroimage.2009.10.003

Saha, P., & Sarkar, D. (2022). Characterization and classifcation of ADHD subtypes: an Approach based on the nodal distribution of Eigenvector Centrality and Classifcation Tree Model. Child Psychiatry & Human Development. https://doi.org/10.1007/s10578-022-01432-6.CrossRef

Schaer, M., Ottet, M. C., Scariati, E., Dukes, D., Franchini, M., Eliez, S., & Glaser, B. (2013). Decreased frontal gyrification correlates with altered connectivity in children with autism. Frontiers In Human Neuroscience, 7, 750.CrossRefPubMedPubMedCentral

Schumann, C. M., Bloss, C. S., Barnes, C. C., Wideman, G. M., Carper, R. A., Akshoomoff, N., Pierce, K., Hagler, D., Schork, N., Lord, C., & Courchesne, E. (2010). Longitudinal magnetic resonance imaging study of cortical development through early childhood in autism. Journal Of Neuroscience, 30, 4419–4427.CrossRefPubMed

Siqueira, A. S., Junior, C. E. B., Comfort, W. E., Rohde, L. A., & Sato, J. R. (2014). Abnormal Functional Resting-State Networks in ADHD: Graph Theory and Pattern Recognition Analysis of fMRI Data. Biomed Res Int. 2014, 380531. doi: https://doi.org/10.1155/2014/380531

Soorya, L., Kolevzon, A., Zweifach, J., Lim, T., Dobry, Y., Schwartz, L., Frank, Y., et al. (2013). Prospective investigation of autism and genotype-phenotype correlations in 22q13 deletion syndrome and SHANK3 deficiency. Mol Autism, 4(1), 18. https://doi.org/10.1186/2040-2392-4-18.CrossRefPubMedPubMedCentral

Uddin, L. Q., Supekar, K., & Menon, V. (2013). Reconceptualizing functional brain connectivity in autism from a developmental perspective. Frontiers In Human Neuroscience, 7, 458.CrossRefPubMedPubMedCentral

Wallace, G. L., Robustelli, B., Dankner, N., Kenworthy, L., Giedd, J. N., & Martin, A. (2013). Increased gyrification, but comparable surface area in adolescents with autism spectrum disorders. Brain, 136, 1956–1967.CrossRefPubMedPubMedCentral

Wang, A. T., Lee, S. S., Sigman, M., & Dapretto, M. (2006). Neural basis of irony comprehension in children with autism: the role of prosody and context. Brain, 129, 932–943.CrossRefPubMed

Zhang, B., Tian, Y., & Zhang, Z. (2014). Network Biology in Medicine and Beyond. Circulation. Cardiovascular Genetics, 7(4), 536–547. https://doi.org/10.1161/CIRCGENETICS.113.000123.CrossRefPubMedPubMedCentral

Zuo, X. N., Ehmke, R., Mennes, M., Imperati, D., Castellanos, F. X., Sporns, O., et al. (2012). Network centrality in the human functional connectome. Cerebral Cortex, 22, 1862–1875. https://doi.org/10.1093/cercor/bhr269.CrossRefPubMed

Titel: Eigenvector Centrality Characterization on fMRI Data: Gender and Node Differences in Normal and ASD Subjects
Author name
Auteur: Papri Saha
Publicatiedatum: 04-05-2023
Uitgeverij: Springer US
Gepubliceerd in: Journal of Autism and Developmental Disorders / Uitgave 7/2024
Print ISSN: 0162-3257
Elektronisch ISSN: 1573-3432
DOI: https://doi.org/10.1007/s10803-023-05922-x

Andere artikelen Uitgave 7/2024

Stumbling Block in Providing Physical Activity Support Among Parents of Children with Autism Spectrum Disorder: A Moderated Mediation Analysis

Original Paper

Dual Identification: Trajectories to English Proficiency for English Learners with Autism Spectrum Disorder

Open Access
Original Paper

Developmental Skills Moderate the Association Between Core Autism Features and Adaptive Behaviour in Early Childhood

Open Access
Original Paper

Economic Evaluation of anti-epileptic Medicines for Autistic Children with Epilepsy

Open Access
Original Paper

Predictors of Developmental and Adaptive Behaviour Outcomes in Response to Early Intensive Behavioural Intervention and the Early Start Denver Model

Open Access
Original Paper

County-Level Prevalence Estimates of Autism Spectrum Disorder in Children in the United States

Original Paper