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The effect of high-order interactions on the functional brain networks of boys with ADHD

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Abstract

Investigating the functional connectivities in the brain networks of individuals with attention deficit hyperactivity disorder (ADHD) has long intrigued researchers. ADHD individuals have defects in recognizing others’facial emotions, resulting in inappropriate social interactions. While great attention has been paid to examining the pairwise interactions between various brain regions in individuals with ADHD, further exploration is required to investigate the impact of simultaneous interactions involving more than two brain regions on ADHD. To fill this research gap, the higher-order interactions of the brain networks of ADHD and healthy boys while observing facial emotions are analyzed in this study. Weighted brain hyper-networks are constructed based on the maximum cliques of the brain networks as hyperlinks. The statistical analysis of topological features extracted from the boys’brain hyper-networks revealed significant differences \((P-values < 0.05)\) between the ADHD and healthy groups in the frontal, right temporal, and occipital brain regions. These findings may represent the defects in the higher-order interactions of brain networks in ADHD boys while processing facial images, emotions, and vision. It is hoped this study can help us gain an understanding of the complicated behavior of brain networks under the influence of ADHD.

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Data availability statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

References

  1. Z. Wang, F.E. Alsaadi, V.T. Pham, Synchronization in a multilayer neuronal network: Effect of time delays. Eur. Phys. J. Spec. Top. 228, 2391–2403 (2019)

    Article  ADS  Google Scholar 

  2. Zhen Wang, Fatemeh Parastesh, Karthikeyan Rajagopal, Ibrahim Ismael Hamarash, Iqtadar Hussain. Delay-induced synchronization in two coupled chaotic memristive hopfield neural networks. Chaos, Solitons & Fractals, 134:109702, (2020)

  3. Z. Wang, S. Baruni, F. Parastesh, S. Jafari, D. Ghosh, M. Perc, I. Hussain, Chimeras in an adaptive neuronal network with burst-timing-dependent plasticity. Neurocomputing 406, 117–126 (2020)

    Article  Google Scholar 

  4. S. Ansarinasab, F. Nazarimehr, F. Ghassemi, D. Ghosh, S. Jafari, Spatial dynamics of swarmalators’ movements. Appl. Math. Comput. 468, 128508 (2024)

    MathSciNet  Google Scholar 

  5. S. Ansarinasab, F. Ghassemi, F. Nazarimehr, D. Ghosh, S. Jafari, Phase synchronization in cryptocurrency network and its features. International Journal of Modern Physics C (IJMPC) 35(02), 1–21 (2024)

    Google Scholar 

  6. H. Dini, M.S.E. Sendi, Investigation of brain functional networks in children suffering from attention deficit hyperactivity disorder. Brain Topogr. 33, 733–750 (2020)

    Article  Google Scholar 

  7. Korosh Mahmoodi, Scott E Kerick, Paolo Grigolini, Piotr J Franaszczuk, Bruce J West. Complexity synchronization: a measure of interaction between the brain, heart and lungs. Scientific Reports, 13(1):11433, (2023)

  8. Jian Kang, Janarthanan Ramadoss, Zhen Wang, Ahmed M Ali Ali. Complete synchronization analysis of neocortical network model. The European Physical Journal Special Topics, 231(22):4037–4048, (2022)

  9. Jeanette C Mostert, Elena Shumskaya, Maarten Mennes, A Marten H Onnink, Martine Hoogman, Cornelis C Kan, Alejandro Arias Vasquez, Jan Buitelaar, Barbara Franke, David G Norris. Characterising resting-state functional connectivity in a large sample of adults with adhd. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 67:82–91, (2016)

  10. S. Ansarinasab, S. Panahi, F. Ghassemi, D. Ghosh, S. Jafari, Synchronization stability analysis of functional brain networks in boys with adhd during facial emotions processing. Physica A 603, 127848 (2022)

    Article  MathSciNet  Google Scholar 

  11. Theresa S Emser, Blair A Johnston, J Douglas Steele, Sandra Kooij, Lisa Thorell, Hanna Christiansen. Assessing adhd symptoms in children and adults: evaluating the role of objective measures. Behavioral and Brain Functions, 14(1):1–14, (2018)

  12. Mehdi Tehrani-Doost, Gholamreza Noorazar, Zahra Shahrivar, Anahita Khorrami Banaraki, Parvane Farhad Beigi, Nahid Noorian. Is emotion recognition related to core symptoms of childhood adhd? Journal of the Canadian Academy of child and Adolescent Psychiatry, 26(1):31, (2017)

  13. Sheida Ansari Nasab, Shirin Panahi, Farnaz Ghassemi, Sajad Jafari, Karthikeyan Rajagopal, Dibakar Ghosh, Matjaž Perc. Functional neuronal networks reveal emotional processing differences in children with adhd. Cognitive Neurodynamics, pages 1–10, (2021)

  14. S. Ansarinasab, F. Ghassemi, Z. Tabanfar, S. Jafari, Investigation of phase synchronization in functional brain networks of children with adhd using nonlinear recurrence measure. J. Theor. Biol. 560, 111381 (2023)

    Article  Google Scholar 

  15. S. Ansarinasab, F. Parastesh, F. Ghassemi, K. Rajagopal, S. Jafari, D. Ghosh, Synchronization in functional brain networks of children suffering from adhd based on hindmarsh-rose neuronal model. Comput. Biol. Med. 152, 106461 (2023)

    Article  Google Scholar 

  16. Shania Mereen Soman, Nandita Vijayakumar, Phoebe Thomson, Gareth Ball, Christian Hyde, Timothy J Silk. Functional and structural brain network development in children with attention deficit hyperactivity disorder. Human Brain Mapping, (2023)

  17. Qiwen Lin, Yafei Shi, Huiyuan Huang, Bingqing Jiao, Changyi Kuang, Jiawen Chen, Yuyang Rao, Yunpeng Zhu, Wenting Liu, Ruiwang Huang, et al. Functional brain network alterations in the co-occurrence of autism spectrum disorder and attention deficit hyperactivity disorder. European Child & Adolescent Psychiatry, pages 1–12, (2023)

  18. Z. Zhu, H. Wang, H. Bi, J. Lv, X. Zhang, S. Wang, L. Zou, Dynamic functional connectivity changes of resting-state brain network in attention-deficit/hyperactivity disorder. Behav. Brain Res. 437, 114121 (2023)

    Article  Google Scholar 

  19. M. Chen, D. Veeman, Z. Wang, A. Karthikeyan, Chimera states in a network of identical oscillators with symmetric coexisting attractors. Eur. Phys. J. Spec. Top. 231(11–12), 2163–2171 (2022)

    Article  Google Scholar 

  20. Yuduo Zhang, Zhichao Lian, Chanying Huang. A multilayer sparse representation of dynamic brain functional network based on hypergraph theory for adhd classification. In Intelligence Science and Big Data Engineering. Big Data and Machine Learning: 9th International Conference, IScIDE 2019, Nanjing, China, October 17–20, 2019, Proceedings, Part II 9, pages 325–334. Springer, (2019)

  21. Z. Wang, H. Tian, O. Krejcar, H. Namazi, Synchronization in a network of map-based neurons with memristive synapse. The European Physical Journal Special Topics 231(22–23), 4057–4064 (2022)

    Article  ADS  Google Scholar 

  22. B. Jie, C.-Y. Wee, D. Shen, D. Zhang, Hyper-connectivity of functional networks for brain disease diagnosis. Med. Image Anal. 32, 84–100 (2016)

    Article  Google Scholar 

  23. Chen Zu, Yue Gao, Brent Munsell, Minjeong Kim, Ziwen Peng, Jessica R Cohen, Daoqiang Zhang, Guorong Wu. Identifying disease-related subnetwork connectome biomarkers by sparse hypergraph learning. Brain imaging and behavior, 13:879–892, (2019)

  24. M. Li, M. Qiu, L. Zhu, W. Kong, Feature hypergraph representation learning on spatial-temporal correlations for eeg emotion recognition. Cogn. Neurodyn. 17(5), 1271–1281 (2023)

    Article  Google Scholar 

  25. Junjie Zhu, Yuxuan Wei, Yifan Feng, Xibin Zhao, Yue Gao. Physiological signals-based emotion recognition via high-order correlation learning. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 15(3s):1–18, (2019)

  26. Jingzhi Shao, Junjie Zhu, Yuxuan Wei, Yifan Feng, Xibin Zhao. Emotion recognition by edge-weighted hypergraph neural network. In 2019 IEEE International Conference on Image Processing (ICIP), pages 2144–2148. IEEE, (2019)

  27. C Keith Conners, Gill Sitarenios, James DA Parker, Jeffery N Epstein. The revised conners’ parent rating scale (cprs-r): factor structure, reliability, and criterion validity. Journal of abnormal child psychology, 26:257–268, (1998)

  28. S. Phadikar, N. Sinha, R. Ghosh, Automatic eeg eyeblink artefact identification and removal technique using independent component analysis in combination with support vector machines and denoising autoencoder. IET Signal Proc. 14(6), 396–405 (2020)

    Article  Google Scholar 

  29. Mahdiyeh Sarraf Razavi, Mehdi Tehranidoost, Farnaz Ghassemi, Parivash Purabassi, Athena Taymourtash. Emotional face recognition in children with attention deficit/hyperactivity disorder: Evidence from event related gamma oscillation. Basic and Clinical Neuroscience, 8(5):419, (2017)

  30. M. Balconi, U. Pozzoli, Event-related oscillations (eros) and event-related potentials (erps) comparison in facial expression recognition. J. Neuropsychol. 1(2), 283–294 (2007)

    Article  Google Scholar 

  31. Ronald Gould. Graph theory. Courier Corporation, (2012)

  32. S. Wallot, D. Mønster, Calculation of average mutual information (ami) and false-nearest neighbors (fnn) for the estimation of embedding parameters of multidimensional time series in matlab. Front. Psychol. 9, 1679 (2018)

    Article  Google Scholar 

  33. P. Di Luzio, L. Tarasi, J. Silvanto, A. Avenanti, V. Romei, Human perceptual and metacognitive decision-making rely on distinct brain networks. PLoS Biol. 20(8), e3001750 (2022)

    Article  Google Scholar 

  34. Issues and recommendations, Martijn P van den Heuvel, Siemon C de Lange, Andrew Zalesky, Caio Seguin, BT Thomas Yeo, and Ruben Schmidt. Proportional thresholding in resting-state fmri functional connectivity networks and consequences for patient-control connectome studies. Neuroimage 152, 437–449 (2017)

    Article  Google Scholar 

  35. Alain Bretto. Hypergraph theory. An introduction. Mathematical Engineering. Cham: Springer, 1, (2013)

  36. Richard F Betzel, Maxwell A Bertolero, Evan M Gordon, Caterina Gratton, Nico UF Dosenbach, and Danielle S Bassett. The community structure of functional brain networks exhibits scale-specific patterns of inter-and intra-subject variability. Neuroimage, 202:115990, (2019)

  37. O. Sporns, Structure and function of complex brain networks. Dialogues Clin. Neurosci. 15(3), 247–262 (2013)

    Article  Google Scholar 

  38. David Eppstein, Maarten Löffler, Darren Strash. Listing all maximal cliques in sparse graphs in near-optimal time. In Algorithms and Computation: 21st International Symposium, ISAAC 2010, Jeju Island, Korea, December 15-17, 2010, Proceedings, Part I 21, pages 403–414. Springer, (2010)

  39. Jeffrey Wildman. Bron-kerbosch maximal clique finding algorithm. Matlab Central File Exchange. Retrived, 27, (2011)

  40. X. Shao, W. Kong, S. Sun, N. Li, X. Li, H. Bin, Analysis of functional connectivity in depression based on a weighted hyper-network method. J. Neural Eng. 20(1), 016023 (2023)

    Article  ADS  Google Scholar 

  41. Hubert W Lilliefors. On the kolmogorov-smirnov test for normality with mean and variance unknown. Journal of the American statistical Association, 62(318):399–402, (1967)

  42. Y. Benjamini, Y. Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. Roy. Stat. Soc.: Ser. B (Methodol.) 57(1), 289–300 (1995)

    MathSciNet  Google Scholar 

  43. C.G. Phillips, S. Zeki, H.B. Barlow, Localization of function in the cerebral cortex: past, present and future. Brain 107(1), 328–361 (1984)

    Article  Google Scholar 

  44. V. Borghesani, J. Narvid, G. Battistella, W. Shwe, C. Watson, R.J. Binney, V. Sturm, Z. Miller, M.L. Mandelli, B. Miller, M.L. Gorno-Tempini, “Looks familiar, but I do not know who she is”: The role of the anterior right temporal lobe in famous face recognition. Cortex 115, 72–85 (2019)

    Article  Google Scholar 

  45. J. Doyon, B. Milner, Right temporal-lobe contribution to global visual processing. Neuropsychologia 29(5), 343–360 (1991)

    Article  Google Scholar 

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Acknowledgements

This paper is supported by the National Natural Science Foundation of China (22278338, 12172281), the Natural Science Basic Research Program of Shaanxi (2023-JC-QN-0090, 2024JC-YBMS-064, 2024JC-YBMS-068), the Scientific Research Program Funded by Education Department of Shaanxi Provincial Government (23JK0706), the Fund of the Science and Technology Innovation Team of Shaanxi (2022TD-61), the Support Plan for Sanqin Scholars Innovation Team in Shaanxi Province of China, the Fund of the Youth Innovation Team of Shaanxi Universities and the Scientific Research Foundation of Xijing University (XJ230108, XJ21B01). The authors also express their gratitude to the reviewers for their insightful comments.

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Authors and Affiliations

  1. Xi’an Key Laboratory of Human–Machine Integration and Control Technology for Intelligent Rehabilitation, School of Computer Science, Xijing University, Xi’an, 710123, People’s Republic of China

    Xiaojian Xi, Jianhui Li, Huaigu Tian & Rui Yang

  2. School of Mathematics and Computer Science, Yan’an University, Yan’an, 716000, People’s Republic of China

    Zhen Wang

  3. Shaanxi International Joint Research Center for Applied Technology of Controllable Neutron Source, Xijing University, Xi’an, 710123, People’s Republic of China

    Zhen Wang & Huaigu Tian

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  1. Xiaojian Xi
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Correspondence to Zhen Wang.

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Xi, X., Li, J., Wang, Z. et al. The effect of high-order interactions on the functional brain networks of boys with ADHD. Eur. Phys. J. Spec. Top. (2024). https://doi.org/10.1140/epjs/s11734-024-01161-y

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