Abstract
Neuroimaging studies have demonstrated that autism spectrum disorder (ASD) is accompanied by abnormal functional and structural features in specific brain regions of the default mode network (DMN). However, little is known about the alterations of the topological organization and the functional connectivity (FC) of the DMN in ASD patients. Thirty-seven ASD patients and 38 healthy control (HC) participants underwent a resting-state functional magnetic resonance imaging scan. Twenty DMN subregions were specifically selected to construct the DMN architecture. We applied graph theory approaches to the topological configuration and compare the FC patterns of the DMN. We then examined the relationships between the neuroimaging measures of the DMN and clinical characteristics in patients with ASD. The current study revealed that both the ASD and HC participants showed a small-world regimen in the DMN; however there were no significant differences in global network measures. Compared with the HC group, the ASD group exhibited significantly decreased nodal centralities in the bilateral anterior medial prefrontal cortex and increased nodal centralities in the right lateral temporal cortex and the right retrosplenial cortex. Patients with ASD displayed significantly reduced and increased FC within the DMN. Our findings demonstrated that ASD patients showed a pattern of disrupted FC metrics and nodal network metrics in the DMN, which could be a potential biomarker for objective ASD diagnoses and for the level of autism spectrum traits.
Highlights
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We used graph theoretical approaches and functional connectivity (FC) to investigate the topological configuration and FC patterns of the DMN in ASD.
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The current study revealed that both ASD and HC participants exhibited small-world regimes in the DMN, however there were no significant differences in global network measures.
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The ASD group showed abnormal nodal centralities in the bilateral aMPFC, the right LTC and the Rsp of the DMN, and ASD was characterized by altered FC patterns, including decreased and increased FC within the DMN.
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References
Achard, S., & Bullmore, E. (2007). Efficiency and cost of economical brain functional networks. PLoS Computational Biology, 3, e17.
Alaerts, K., Geerlings, F., Herremans, L., Swinnen, S. P., Verhoeven, J., et al. (2015). Functional Organization of the Action Observation Network in autism: A graph theory approach. PLoS One, 10, e137020.
Andrews-Hanna, J. R., Reidler, J. S., Sepulcre, J., Poulin, R., & Buckner, R. L. (2010). Functional-anatomic fractionation of the brain’s default network. Neuron, 65, 550–562.
Assaf, M., Jagannathan, K., Calhoun, V. D., Miller, L., Stevens, M. C., Sahl, R., O'Boyle, J. G., Schultz, R. T., & Pearlson, G. D. (2010). Abnormal functional connectivity of default mode sub-networks in autism spectrum disorder patients. NEUROIMAGE, 53, 247–256.
Baio, J. W. L. C. (2018). Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years — Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2014. In Prevalence of autism Spectrum disorder among children aged 8 years — Autism and developmental disabilities monitoring network, 11 sites, United States, 2014.
Bullmore, E., & Sporns, O. (2009). Complex brain networks: Graph theoretical analysis of structural and functional systems. Nature Reviews. Neuroscience, 10, 186–198.
Chai, X. J., Alfonso Nieto, C. Ó., Dost, O., & Susan, W. G. (2012). Anticorrelations in resting state networks without global signal regression. NEUROIMAGE, 59, 1420–1428.
Chen, L., Fan, X., Li, H., Ye, C., Yu, H., Gong, H., Zeng, X., Peng, D., & Yan, L. (2018). Topological reorganization of the default mode network in severe male obstructive sleep apnea. Frontiers in Neurology, 9, 363.
Constantino, J. N. (2013). Social Responsiveness Scale. In Social responsiveness scale.
Constantino, J. N., Abbacchi, A. M., Lavesser, P. D., Hannah, R., Leah, G., et al. (2009). Developmental course of autistic social impairment in males. Development and Psychopathology, 21, 127–138.
Dijk, K. R. A. V., Trey, H., Archana, V., Evans, K. C., Lazar, S. W., & Buckner, R. L. (2010). Intrinsic functional connectivity as a tool for human connectomics: Theory, properties, and optimization. Journal of Neurophysiology, 103, 297–321.
Eilam-Stock, T., Wu, T., Spagna, A., Egan, L. J., & Fan, J. (2016). Neuroanatomical alterations in high-functioning adults with autism Spectrum disorder. FRONT NEUROSCI-SWITZ, 10, 237.
Feng, L., Zhuo, C., & Yu, C. (2016). Altered Cerebral Blood Flow Covariance Network in Schizophrenia. FRONT NEUROSCI-SWITZ, 10.
Fishman, I., Keown, C. L., Lincoln, A. J., Pineda, J. A., & Müller, R. A. (2014). Atypical cross talk between mentalizing and mirror neuron networks in autism spectrum disorder. JAMA Psychiatry, 71, 751–760.
Goto, M., Aoki, S., Hayashi, N., Miyati, T., Takao, H., et al. (2013). Diffeomorphic anatomical registration through Exponentiated lie algebra provides reduced effect of scanner for cortex volumetry with atlas-based method in healthy subjects. NEURORADIOLOGY, 55, 869–875.
Greicius, M. D., Ben, K., Reiss, A. L., & Vinod, M. (2003). Functional connectivity in the resting brain: A network analysis of the default mode hypothesis. Proceedings of the National Academy of Sciences of the United States of America, 100, 253–258.
Hirotaka, K., Masao, O., Toshio, M., Makoto, I., Yukiko, M., et al. (2010). Smaller insula and inferior frontal volumes in young adults with pervasive developmental disorders. Neuroimage, 50, 1357–1363.
Ishitobi, M., Kosaka, H., Omori, M., Matsumura, Y., Munesue, T., Mizukami, K., Shimoyama, T., Murata, T., Sadato, N., Okazawa, H., & Wada, Y. (2011). Differential amygdala response to lower face in patients with autistic spectrum disorders: An fMRI study. Res Autism Spect Dis, 5, 910–919.
Jung, M., Kosaka, H., Saito, D. N., Ishitobi, M., Morita, T., Inohara, K., Asano, M., Arai, S., Munesue, T., Tomoda, A., Wada, Y., Sadato, N., Okazawa, H., & Iidaka, T. (2014). Default mode network in young male adults with autism spectrum disorder: Relationship with autism spectrum traits. Mol Autism, 5, 35.
Kaiser, M., & Hilgetag, C. C. (2006). Nonoptimal component placement, but short processing paths, due to long-distance projections in neural systems. PLoS Computational Biology, 2, e95.
Kennedy, D. P., & Courchesne, E. (2008). Functional abnormalities of the default network during self- and other-reflection in autism. Social Cognitive and Affective Neuroscience, 3, 177–190.
Keown, C. L., Datko, M. C., Chen, C. P., Maximo, J. O., Jahedi, A., & Müller, R. A. (2017). Network organization is globally atypical in autism: A graph theory study of intrinsic functional connectivity. Biological Psychiatry Cognitive Neuroscience & Neuroimaging, 2, 66–75.
Kim, S. H., Hus, V., & Lord, C. (2013). Autism Diagnostic Interview-Revised. In Autism diagnostic interview-revised.
Liu F, Tian H, Li J, Li S, Zhuo C. 2018. Altered voxel-wise gray matter structural brain networks in schizophrenia: Association with brain genetic expression pattern. Brain Imaging & Behavior:1–10.
Liu, F., Wang, Y., Li, M., Wang, W., Li, R., Zhang, Z., Lu, G., & Chen, H. (2017). Dynamic functional network connectivity in idiopathic generalized epilepsy with generalized tonic-clonic seizure. Human Brain Mapping, 38, 957–973.
Liu, F., Zhuo, C., & Yu, C. (2016). Altered Cerebral Blood Flow Covariance Network in Schizophrenia. Front Neurosci-Switz, 10.
Martino, A. D., C-G, Y., Li, Q., Denio, E., Castellanos, F. X., et al. (2014). The autism brain imaging data exchange: Towards a large-scale evaluation of the intrinsic brain architecture in autism. Mol Psychiatr, 19, 659–667.
Micheloyannis, S. (2012). Graph-based network analysis in schizophrenia. World Journal of Psychiatry, 2, 1–12.
Monk, C. S., Peltier, S. J., Jillian Lee, W., Shih-Jen, W., Melisa, C., et al. (2009). Abnormalities of intrinsic functional connectivity in autism spectrum disorders. Neuroimage, 47, 764–772.
Morita, T., Kosaka, H., Saito, D. N., Ishitobi, M., Munesue, T., Itakura, S., Omori, M., Okazawa, H., Wada, Y., & Sadato, N. (2012). Emotional responses associated with self-face processing in individuals with autism spectrum disorders: An fMRI study. Social Neuroscience, 7, 223–239.
Raichle, M. E. (2007). A default mode of brain function: A brief history of an evolving idea. Neuroimage, 37, 1083–1090.
Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. NEUROIMAGE, 52, 1059–1069.
Rudie, J. D., Brown, J. A., Beck-Pancer, D., Hernandez, L. M., Dennis, E. L., Thompson, P. M., Bookheimer, S. Y., & Dapretto, M. (2013). Altered functional and structural brain network organization in autism. Neuroimage Clinical, 2, 79–94.
Rudie, J. D., Zarrar, S., Hernandez, L. M., Colich, N. L., Bookheimer, S. Y., et al. (2012). Reduced functional integration and segregation of distributed neural systems underlying social and emotional information processing in autism spectrum disorders. Cerebral Cortex, 22, 1025–1037.
Sam, W. (2011). Distortions and disconnections: Disrupted brain connectivity in autism. Brain & Cognition, 75, 18–28.
Schilbach, L., Eickhoff, S. B., Rotarska-Jagiela, A., Fink, G. R., & Kai, V. (2008). Minds at rest? Social cognition as the default mode of cognizing and its putative relationship to the “default system” of the brain. Consciousness & Cognition, 17, 457–467.
Schulte-Rüther, M., Greimel, E., Markowitsch, H. J., Kamp-Becker, I., Remschmidt, H., Fink, G. R., & Piefke, M. (2011). Dysfunctions in brain networks supporting empathy: An fMRI study in adults with autism spectrum disorders. Social Neuroscience, 6, 1–21.
Suo, X., Lei, D., Li, K., Chen, F., Li, F., Li, L., Huang, X., Lui, S., Li, L., Kemp, G. J., & Gong, Q. (2015). Disrupted brain network topology in pediatric posttraumatic stress disorder: A resting-state fMRI study. Human Brain Mapping, 36, 3677–3686.
Tsakanikos, E., Underwood, L., Kravariti, E., Bouras, N., & Mccarthy, J. (2011). Gender differences in co-morbid psychopathology and clinical management in adults with autism spectrum disorders. Res Autism Spect Dis, 5, 803–808.
Uddin, L. Q., Kelly, A. M. C., Biswal, B. B., Castellanos, F. X., & Milham, M. P. (2010). Functional connectivity of default mode network components: Correlation, Anticorrelation, and causality. Human Brain Mapping, 30, 625–637.
Uddin, L. Q., Menon, V., Young, C. B., Ryali, S., Chen, T., Khouzam, A., Minshew, N. J., & Hardan, A. Y. (2011). Multivariate searchlight classification of structural magnetic resonance imaging in children and adolescents with autism. Biological Psychiatry, 70, 833–841.
Valk, S. L., Di, M. A., Milham, M. P., & Bernhardt, B. C. (2015). Multicenter mapping of structural network alterations in autism. Human Brain Mapping, 36, 2364–2373.
Van Dijk, K. R., Sabuncu, M. R., & Buckner, R. L. (2012). The influence of head motion on intrinsic functional connectivity MRI. Neuroimage, 59, 431–438.
Vissers, M. E., Cohen, M. X., & Geurts, H. M. (2012). Brain connectivity and high functioning autism: A promising path of research that needs refined models, methodological convergence, and stronger behavioral links. Neuroscience and Biobehavioral Reviews, 36, 604–625.
Wang, J., Wang, X., Xia, M., Liao, X., Evans, A., & He, Y. (2015). GRETNA: A graph theoretical network analysis toolbox for imaging connectomics. Frontiers in Human Neuroscience, 9, 386.
Wang, J., Zuo, X., & Yong, H. (2010). Graph-based network analysis of resting-state functional MRI. Frontiers in Systems Neuroscience, 4, 16.
Weng, S. J., Wiggins, J. L., Peltier, S. J., Carrasco, M., Risi, S., Lord, C., & Monk, C. S. (2010). Alterations of resting state functional connectivity in the default network in adolescents with autism spectrum disorders. Brain Research, 1313, 202–214.
Yan, C. G., Wang, X. D., Zuo, X. N., & Zang, Y. F. (2016). DPABI: Data Processing & Analysis for (resting-state) brain imaging. Neuroinformatics, 14, 339–351.
Yerys, B. E., Gordon, E. M., Abrams, D. N., Satterthwaite, T. D., Weinblatt, R., Jankowski, K. F., Strang, J., Kenworthy, L., Gaillard, W. D., & Vaidya, C. J. (2015). Default mode network segregation and social deficits in autism spectrum disorder: Evidence from non-medicated children. Neuroimage Clinical, 9, 223–232.
Yong, H., & Alan, E. (2010). Graph theoretical modeling of brain connectivity. Current Opinion in Neurology, 23, 341–350.
Zalesky, A., Fornito, A., & Bullmore, E. T. (2010). Network-based statistic: Identifying differences in brain networks. Neuroimage, 53, 1197–1207.
Acknowledgements
We acknowledge the Autism Brain Imaging Data Exchange (ABIDE) II or the acquisition of the imaging data. We acknowledge financial support from the National Natural Science Foundation of China (81571664, 81871323, 81801665), the National Natural Science Foundation of Guangdong Province (2018B030311024), the Scientific Research General Project of Guangzhou Science Technology and Innovation Commission (201707010328), and the China Postdoctoral Science Foundation (2016 M600145).
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Chen, L., Chen, Y., Zheng, H. et al. Changes in the topological organization of the default mode network in autism spectrum disorder. Brain Imaging and Behavior 15, 1058–1067 (2021). https://doi.org/10.1007/s11682-020-00312-8
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DOI: https://doi.org/10.1007/s11682-020-00312-8