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Review
Dynamic functional connectivity in autism spectrum disorders: applications and research advances
WU Guangrong  ZHANG Guomin  XU Yuanyuan  YANG Wei 

Cite this article as: WU G R, ZHANG G M, XU Y Y, et al. Dynamic functional connectivity in autism spectrum disorders: applications and research advances[J]. Chin J Magn Reson Imaging, 2024, 15(6): 153-158. DOI:10.12015/issn.1674-8034.2024.06.024.


[Abstract] Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder resulting from impaired information flow in human brain systems, highly heritable and associated with impaired dynamic functional connectivity (DFC). Individuals with ASD are one of the more far-reaching child psychiatric disorders, and the families of diagnosed children are faced with multiple stressors and challenges from financial, emotional, and social perspectives. Previous research on ASD has been based on resting-state functional connectivity (SFC), but SFC has largely failed to take into account the presence and potential of temporal variability to impact brain function. In recent years, DFC has been widely used in ASD studies because it can accurately capture the fluctuations of functional connectivity (FC) over time and reveal the transitions between different FC states. In this paper, we review some common and newer methods of DFC, such as the sliding-window (SW) , the hidden Markov model (HMM), and the leading eigenvector dynamics analysis (LEiDA), as well as the applications and recent research progress of these methods in ASD, and summarize and compare the advantages and shortcomings of these methods. This review expects to provide a new way for early diagnosis and personalized treatment of ASD by summarizing the DFC methods and their applications. By analyzing DFC patterns, researchers are able to identify specific connective features associated with ASD, and are expected to develop DFC-based biomarkers to improve the diagnostic accuracy and reliability of ASD.
[Keywords] autism spectrum disorder;magnetic resonance imaging;functional magnetic resonance imaging;brain network;functional network;dynamic functional connectivity

WU Guangrong   ZHANG Guomin   XU Yuanyuan   YANG Wei*  

Department of Radiology, the Third Affiliated Hospital of Zunyi Medical University (the First People's Hospital of Zunyi), Zunyi 563000, China

Corresponding author: YANG W, E-mail: coxsackie@163.com

Conflicts of interest   None.

Received  2024-02-22
Accepted  2024-06-05
DOI: 10.12015/issn.1674-8034.2024.06.024
Cite this article as: WU G R, ZHANG G M, XU Y Y, et al. Dynamic functional connectivity in autism spectrum disorders: applications and research advances[J]. Chin J Magn Reson Imaging, 2024, 15(6): 153-158. DOI:10.12015/issn.1674-8034.2024.06.024.

[1]
LAI M C, LOMBARDO M V, BARON-COHEN S. Autism[J]. Lancet, 2014, 383(9920): 896-910. DOI: 10.1016/s0140-6736(13)61539-1.
[2]
YANG T, CHEN L, DAI Y, et al. Vitamin A status is more commonly associated with symptoms and neurodevelopment in boys with autism spectrum disorders-a multicenter study in China[J/OL]. Front Nutr, 2022, 9: 851980 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/35495950/. DOI: 10.3389/fnut.2022.851980.
[3]
SALARI N, RASOULPOOR S, RASOULPOOR S, et al. The global prevalence of autism spectrum disorder: a comprehensive systematic review and meta-analysis[J/OL]. Ital J Pediatr, 2022, 48(1): 112 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/35804408/. DOI: 10.1186/s13052-022-01310-w.
[4]
ZHOU H, XU X, YAN W L, et al. Prevalence of autism spectrum disorder in China: a nationwide multi-center population-based study among children aged 6 to 12 years[J]. Neurosci Bull, 2020, 36(9): 961-971. DOI: 10.1007/s12264-020-00530-6.
[5]
XIE Y P, XU Z L, XIA M R, et al. Alterations in connectome dynamics in autism spectrum disorder: a harmonized mega- and meta-analysis study using the autism brain imaging data exchange dataset[J]. Biol Psychiatry, 2022, 91(11): 945-955. DOI: 10.1016/j.biopsych.2021.12.004.
[6]
ALLEN E A, DAMARAJU E, PLIS S M, et al. Tracking whole-brain connectivity dynamics in the resting state[J]. Cereb Cortex, 2014, 24(3): 663-676. DOI: 10.1093/cercor/bhs352.
[7]
KALLITSOUNAKI A, WILLIAMS D M. Autism Spectrum Disorder and Gender Dysphoria/Incongruence. A systematic Literature Review and Meta-Analysis[J]. J Autism Dev Disord, 2023, 53(8): 3103-3117. DOI: 10.1007/s10803-022-05517-y.
[8]
PRETI M G, BOLTON T A, VAN DE VILLE D. The dynamic functional connectome: state-of-the-art and perspectives[J/OL]. Neuroimage, 2017, 160: 41-54 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/28034766/. DOI: 10.1016/j.neuroimage.2016.12.061.
[9]
FU Z N, TU Y H, DI X, et al. Transient increased thalamic-sensory connectivity and decreased whole-brain dynamism in autism[J/OL]. Neuroimage, 2019, 190: 191-204 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/29883735/. DOI: 10.1016/j.neuroimage.2018.06.003.
[10]
KUPIS L, ROMERO C, DIRKS B, et al. Evoked and intrinsic brain network dynamics in children with autism spectrum disorder[J/OL]. Neuroimage Clin, 2020, 28: 102396 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/32891039/. DOI: 10.1016/j.nicl.2020.102396.
[11]
GAN C T, JI M, SUN H M, et al. Dynamic functional connectivity reveals hyper-connected pattern and abnormal variability in freezing of gait of Parkinson's disease[J/OL]. Neurobiol Dis, 2023, 185: 106265 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/37597816/. DOI: 10.1016/j.nbd.2023.106265.
[12]
CAO Y Y, SI Q, TONG R J, et al. Abnormal dynamic functional connectivity changes correlated with non-motor symptoms of Parkinson's disease[J/OL]. Front Neurosci, 2023, 17: 1116111 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/37008221/. DOI: 10.3389/fnins.2023.1116111.
[13]
CHEN B, YANG M F, ZHONG X M, et al. Disrupted dynamic functional connectivity of hippocampal subregions mediated the slowed information processing speed in late-life depression[J]. Psychol Med, 2023, 53(14): 1-11. DOI: 10.1017/S0033291722003786.
[14]
JING R X, CHEN P D, WEI Y B, et al. Altered large-scale dynamic connectivity patterns in Alzheimer's disease and mild cognitive impairment patients: a machine learning study[J]. Hum Brain Mapp, 2023, 44(9): 3467-3480. DOI: 10.1002/hbm.26291.
[15]
SENDI M S E, ZENDEHROUH E, FU Z N, et al. Disrupted dynamic functional network connectivity among cognitive control networks in the progression of Alzheimer's disease[J]. Brain Connect, 2023, 13(6): 334-343. DOI: 10.1089/brain.2020.0847.
[16]
WANG B, PAN T T, GUO M, et al. Abnormal dynamic reconfiguration of the large-scale functional network in schizophrenia during the episodic memory task[J]. Cereb Cortex, 2023, 33(7): 4135-4144. DOI: 10.1093/cercor/bhac331.
[17]
YUAN Y M, ZHANG L, ZHANG Z G. A review of methods and clinical applications for dynamic functional connectivity analysis based on resting-state functional magnetic resonance imaging[J]. Chin J Magn Reson Imag, 2018, 9(8): 579-588. DOI: 10.12015/issn.1674-8034.2018.08.005.
[18]
JIE B, LIU M X, SHEN D G. Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease[J/OL]. Med Image Anal, 2018, 47: 81-94 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/29702414/. DOI: 10.1016/j.media.2018.03.013.
[19]
GUO X N, ZHAI G J, LIU J F, et al. Heterogeneity of dynamic synergetic configurations of salience network in children with autism spectrum disorder[J]. Autism Res, 2023, 16(12): 2275-2290. DOI: 10.1002/aur.3037.
[20]
LOHMANN G, ERFURTH K, MÜLLER K, et al. Critical comments on dynamic causal modelling[J/OL]. NeuroImage, 2012, 59: 2322-2329 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/22001162/. DOI: 10.1016/j.neuroimage.2011.09.025.
[21]
FRÄSSLE S, LOMAKINA E I, KASPER L, et al. A generative model of whole-brain effective connectivity[J/OL]. NeuroImage, 2018, 179: 505-529 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/29807151/. DOI: 10.1016/j.neuroimage.2018.05.058.
[22]
FRÄSSLE S, MANJALY Z M, DO C T, et al. Whole-brain estimates of directed connectivity for human connectomics[J/OL]. Neuroimage, 2021, 225: 117491 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/33115664/. DOI: 10.1016/j.neuroimage.2020.117491.
[23]
JIA H B, WU X C, WANG E G. Aberrant dynamic functional connectivity features within default mode network in patients with autism spectrum disorder: evidence from dynamical conditional correlation[J]. Cogn Neurodyn, 2022, 16(2): 391-399. DOI: 10.1007/s11571-021-09723-9.
[24]
JIA H B, WU X C, WU Z Y, et al. Aberrant dynamic minimal spanning tree parameters within default mode network in patients with autism spectrum disorder[J/OL]. Front Psychiatry, 2022, 13: 860348 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/36186871/. DOI: 10.3389/fpsyt.2022.860348.
[25]
VIDAURRE D, QUINN A J, BAKER A P, et al. Spectrally resolved fast transient brain states in electrophysiological data[J/OL]. Neuroimage, 2016, 126: 81-95 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/26631815/. DOI: 10.1016/j.neuroimage.2015.11.047.
[26]
STEVNER A B A, VIDAURRE D, CABRAL J, et al. Discovery of key whole-brain transitions and dynamics during human wakefulness and non-REM sleep[J/OL]. Nat Commun, 2019, 10(1): 1035 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/30833560/. DOI: 10.1038/s41467-019-08934-3.
[27]
LIN P T, ZANG S Y, BAI Y, et al. Reconfiguration of brain network dynamics in autism spectrum disorder based on hidden Markov model[J/OL]. Front Hum Neurosci, 2022, 16: 774921 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/35211000/. DOI: 10.3389/fnhum.2022.774921.
[28]
VIDAURRE D, SMITH S M, WOOLRICH M W. Brain network dynamics are hierarchically organized in time[J]. Proc Natl Acad Sci USA, 2017, 114(48): 12827-12832. DOI: 10.1073/pnas.1705120114.
[29]
FIGUEROA C A, CABRAL J, MOCKING R J T, et al. Altered ability to access a clinically relevant control network in patients remitted from major depressive disorder[J]. Hum Brain Mapp, 2019, 40(9): 2771-2786. DOI: 10.1002/hbm.24559.
[30]
CABRAL J, VIDAURRE D, MARQUES P, et al. Cognitive performance in healthy older adults relates to spontaneous switching between states of functional connectivity during rest[J/OL]. Sci Rep, 2017, 7(1): 5135 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/28698644/. DOI: 10.1038/s41598-017-05425-7.
[31]
LORD L D, EXPERT P, ATASOY S, et al. Dynamical exploration of the repertoire of brain networks at rest is modulated by psilocybin[J/OL]. Neuroimage, 2019, 199: 127-142 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/31132450/. DOI: 10.1016/j.neuroimage.2019.05.060.
[32]
KURTIN D L, SCOTT G, HEBRON H, et al. Task-based differences in brain state dynamics and their relation to cognitive ability[J/OL]. Neuroimage, 2023, 271: 119945 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/36870433/. DOI: 10.1016/j.neuroimage.2023.119945.
[33]
ZHAO F, ZHANG X F, THUNG K H, et al. Constructing multi-view high-order functional connectivity networks for diagnosis of autism spectrum disorder[J]. IEEE Trans Biomed Eng, 2022, 69(3): 1237-1250. DOI: 10.1109/TBME.2021.3122813.
[34]
RAATIKAINEN V, KORHONEN V, BORCHARDT V, et al. Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder[J]. Autism Res, 2020, 13(2): 244-258. DOI: 10.1002/aur.2218.
[35]
AGGARWAL P, GUPTA A. Multivariate graph learning for detecting aberrant connectivity of dynamic brain networks in autism[J/OL]. Med Image Anal, 2019, 56: 11-25 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/31150935/. DOI: 10.1016/j.media.2019.05.007.
[36]
XIE Q S, ZHANG X F, REKIK I, et al. Constructing high-order functional connectivity network based on central moment features for diagnosis of autism spectrum disorder[J/OL]. PeerJ, 2021, 9: e11692 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/34268010/. DOI: 10.7717/peerj.11692.
[37]
LI L, HE C C, JIAN T R, et al. Attenuated link between the medial prefrontal cortex and the amygdala in children with autism spectrum disorder: evidence from effective connectivity within the "social brain"[J/OL]. Prog Neuropsychopharmacol Biol Psychiatry, 2021, 111: 110147 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/33096157/. DOI: 10.1016/j.pnpbp.2020.110147.
[38]
SATO M, NAKAI N, FUJIMA S, et al. Social circuits and their dysfunction in autism spectrum disorder[J]. Mol Psychiatry, 2023, 28(8): 3194-3206. DOI: 10.1038/s41380-023-02201-0.
[39]
LIN Q W, SHI Y F, HUANG H Y, et al. Functional brain network alterations in the co-occurrence of autism spectrum disorder and attention deficit hyperactivity disorder[J]. Eur Child Adolesc Psychiatry, 2024, 33(2): 369-380. DOI: 10.1007/s00787-023-02165-0.
[40]
BATHELT J, GEURTS H M. Difference in default mode network subsystems in autism across childhood and adolescence[J]. Autism, 2021, 25(2): 556-565. DOI: 10.1177/1362361320969258.
[41]
ZHUANG W W, JIA H, LIU Y H, et al. Identification and analysis of autism spectrum disorder via large-scale dynamic functional network connectivity[J]. Autism Res, 2023, 16(8): 1512-1526. DOI: 10.1002/aur.2974.
[42]
ZHAO L, XUE S W, SUN Y K, et al. Altered dynamic functional connectivity of insular subregions could predict symptom severity of male patients with autism spectrum disorder[J/OL]. J Affect Disord, 2022, 299: 504-512 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/34953921/. DOI: 10.1016/j.jad.2021.12.093.
[43]
GUO X N, DUAN X J, CHEN H, et al. Altered inter- and intrahemispheric functional connectivity dynamics in autistic children[J]. Hum Brain Mapp, 2020, 41(2): 419-428. DOI: 10.1002/hbm.24812.
[44]
MENON V. 20 years of the default mode network: a review and synthesis[J]. Neuron, 2023, 111(16): 2469-2487. DOI: 10.1016/j.neuron.2023.04.023.
[45]
GUO X N, DUAN X J, SUCKLING J, et al. Partially impaired functional connectivity states between right anterior insula and default mode network in autism spectrum disorder[J]. Hum Brain Mapp, 2019, 40(4): 1264-1275. DOI: 10.1002/hbm.24447.
[46]
SEVINC G, GURVIT H, SPRENG R N. Salience network engagement with the detection of morally laden information[J]. Soc Cogn Affect Neurosci, 2017, 12(7): 1118-1127. DOI: 10.1093/scan/nsx035.
[47]
UDDIN L Q. Brain mechanisms supporting flexible cognition and behavior in adolescents with autism spectrum disorder[J]. Biol Psychiatry, 2021, 89(2): 172-183. DOI: 10.1016/j.biopsych.2020.05.010.
[48]
YUE X P, ZHANG G, LI X C, et al. Abnormal dynamic functional network connectivity in adults with autism spectrum disorder[J]. Clin Neuroradiol, 2022, 32(4): 1087-1096. DOI: 10.1007/s00062-022-01173-y.
[49]
CHEN Y Y, ULJAREVIC M, NEAL J, et al. Excessive functional coupling with less variability between salience and default mode networks in autism spectrum disorder[J]. Biol Psychiatry Cogn Neurosci Neuroimaging, 2022, 7(9): 876-884. DOI: 10.1016/j.bpsc.2021.11.016.
[50]
GUO X N, CAO Y B, LIU J F, et al. Dysregulated dynamic time-varying triple-network segregation in children with autism spectrum disorder[J]. Cereb Cortex, 2023, 33(9): 5717-5726. DOI: 10.1093/cercor/bhac454.
[51]
GAO Y Y, SUN J W, CHENG L L, et al. Altered resting state dynamic functional connectivity of amygdala subregions in patients with autism spectrum disorder: a multi-site fMRI study[J/OL]. J Affect Disord, 2022, 312: 69-77 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/35710036/. DOI: 10.1016/j.jad.2022.06.011.
[52]
LI Y, ZHU Y Y, NGUCHU B A, et al. Dynamic functional connectivity reveals abnormal variability and hyper-connected pattern in autism spectrum disorder[J]. Autism Res, 2020, 13(2): 230-243. DOI: 10.1002/aur.2212.
[53]
RANDENIYA R, VILARES I, MATTINGLEY J B, et al. Increased functional activity, bottom-up and intrinsic effective connectivity in autism[J/OL]. Neuroimage Clin, 2023, 37: 103293 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/36527995/. DOI: 10.1016/j.nicl.2022.103293.
[54]
NAKAMURA Y, ISHIDA T, TANAKA S C, et al. Distinctive alterations in the mesocorticolimbic circuits in various psychiatric disorders[J]. Psychiatry Clin Neurosci, 2023, 77(6): 345-354. DOI: 10.1111/pcn.13542.
[55]
XIE H, ZHENG C Y, HANDWERKER D A, et al. Efficacy of different dynamic functional connectivity methods to capture cognitively relevant information[J/OL]. Neuroimage, 2019, 188: 502-514 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/30576850/. DOI: 10.1016/j.neuroimage.2018.12.037.
[56]
MASEDU F, VAGNETTI R, PINO M C, et al. Comparison of visual fixation trajectories in toddlers with autism spectrum disorder and typical development: a Markov chain model[J/OL]. Brain Sci, 2021, 12(1): 10 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/35053753/. DOI: 10.3390/brainsci12010010.
[57]
FARINHA M, AMADO C, MORGADO P, et al. Increased excursions to functional networks in schizophrenia in the absence of task[J/OL]. Front Neurosci, 2022, 16: 821179 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/35360175/. DOI: 10.3389/fnins.2022.821179.
[58]
ALONSO MARTÍNEZ S, DECO G, HORST G J TER, et al. The dynamics of functional brain networks associated with depressive symptoms in a nonclinical sample[J/OL]. Front Neural Circuits, 2020, 14: 570583 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/33071760/. DOI: 10.3389/fncir.2020.570583.
[59]
WANG C Y, YANG L, LIN Y N, et al. Alteration of resting-state network dynamics in autism spectrum disorder based on leading eigenvector dynamics analysis[J/OL]. Front Integr Neurosci, 2022, 16: 922577 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/36743477/. DOI: 10.3389/fnint.2022.922577.
[60]
FASANO M C, CABRAL J, STEVNER A, et al. The early adolescent brain on music: analysis of functional dynamics reveals engagement of orbitofrontal cortex reward system[J]. Hum Brain Mapp, 2023, 44(2): 429-446. DOI: 10.1002/hbm.26060.
[61]
LI X Y, ZHANG K, HE X, et al. Structural, functional, and molecular imaging of autism spectrum disorder[J]. Neurosci Bull, 2021, 37(7): 1051-1071. DOI: 10.1007/s12264-021-00673-0.
[62]
MA L, YUAN T F, LI W, et al. Dynamic functional connectivity alterations and their associated gene expression pattern in autism spectrum disorders[J/OL]. Front Neurosci, 2021, 15: 794151 [2024-02-21]. https://pubmed.ncbi.nlm.nih.gov/35082596/. DOI: 10.3389/fnins.2021.794151.
[63]
HYATT C J, WEXLER B E, PITTMAN B, et al. Atypical dynamic functional network connectivity state engagement during social-emotional processing in schizophrenia and autism[J]. Cereb Cortex, 2022, 32(16): 3406-3422. DOI: 10.1093/cercor/bhab423.

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