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[Chinese][PDF]2023
• Review •
The application and progress of dynamic functional connectivity in idiopathic generalized epilepsy
ZHANG Jiaren  GU Xiaoyu  HE Lian  MA Wenmin  WU Guangrong  LI Dongxue  JIANG Lin 

Cite this article as: ZHANG J R, GU X Y, HE L, et al. The application and progress of dynamic functional connectivity in idiopathic generalized epilepsy[J]. Chin J Magn Reson Imaging, 2024, 15(2): 167-171. DOI:10.12015/issn.1674-8034.2024.02.026.


[Abstract] Idiopathic generalized epilepsy (IGE) is a group of generalized epilepsy syndromes closely related to genetic factors, with the main clinical manifestation of generalized seizures, which are manifested as generalized or bilateral symmetrical abnormal discharges on electroencephalogram (EEG), and routine MRI is negative. With the use of new methods of MRI, some progress has been made in the study of the mechanism of IGE occurrence and development, but it is still not fully elucidated. In recent years, dynamic functional connectivity (DFC), as a new network analysis method, has been gradually applied to the neuroscientific study of IGE to analyze the association between cognitive dysfunction and dynamic information transfer and integration, which provides valuable new insights into the developmental mechanism of IGE. Insights. In this paper, we summarize the application and progress of DFC research on IGE in recent years, hoping to provide certain reference for IGE research.
[Keywords] idiopathic generalized epilepsy；magnetic resonance imaging；functional magnetic resonance imaging；brain network；functional network；dynamic functional connectivity；electroencephalography

ZHANG Jiaren1   GU Xiaoyu1   HE Lian2   MA Wenmin1   WU Guangrong1   LI Dongxue1   JIANG Lin1*  

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

2 Department of Radiology, the Second Affiliated Hospital of Zunyi Medical University, Zunyi 563000, China

Corresponding author: JIANG L, E-mail: jlinzmc@163.com

Conflicts of interest   None.

Received  2023-08-16
Accepted  2024-02-05
DOI: 10.12015/issn.1674-8034.2024.02.026
Cite this article as: ZHANG J R, GU X Y, HE L, et al. The application and progress of dynamic functional connectivity in idiopathic generalized epilepsy[J]. Chin J Magn Reson Imaging, 2024, 15(2): 167-171. DOI:10.12015/issn.1674-8034.2024.02.026.

[1]
CAMFIELD P, Incidence CAMFIELD C., prevalence and aetiology of seizures and epilepsy in children[J]. Epileptic Disord, 2015, 17(2): 117-123. DOI: 10.1684/epd.2015.0736.
[2]
HIRSCH E, FRENCH J, SCHEFFER I E, et al. ILAE definition of the idiopathic generalized epilepsy syndromes: position statement by the ilae task force on nosology and definitions[J]. Epilepsia, 2022, 63(6): 1475-1499. DOI: 10.1111/epi.17236.
[3]
GUERRINI R, MARINI C, BARBA C. Generalized epilepsies[J]. Handb Clin Neurol, 2019, 161: 3-15. DOI: 10.1016/B978-0-444-64142-7.00038-2.
[4]
ZHANG Z, LIU G, ZHENG W, et al. Altered dynamic effective connectivity of the default mode network in newly diagnosed drug-naïve juvenile myoclonic epilepsy[J/OL]. Neuroimage Clin, 2020, 28: 102431 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/32950903/. DOI: 10.1016/j.nicl.2020.102431.
[5]
ROYER J, BERNHARDT B C, LARIVIÈRE S, et al. Epilepsy and brain network hubs[J]. Epilepsia, 2022, 63(3): 537-550. DOI: 10.1111/epi.17171.
[6]
GONG J, JIANG S, LI Z, et al. Distinct effects of the basal ganglia and cerebellum on the thalamocortical pathway in idiopathic generalized epilepsy[J]. Hum Brain Mapp, 2021, 42(11): 3440-3449. DOI: 10.1002/hbm.25444.
[7]
FONSECA WALD E L A, KLINKENBERG S, VONCKEN T P C, et al. Cognitive development in absence epilepsy during long-term follow-up[J]. Child Neuropsychol, 2019, 25(8): 1003-1021. DOI: 10.1080/09297049.2019.1614156.
[8]
LURIE D J, KESSLER D, BASSETT D S, et al. Questions and controversies in the study of time-varying functional connectivity in resting fmri[J]. Netw Neurosci, 2020, 4(1): 30-69. DOI: 10.1162/netn_a_00116.
[9]
YANG S, ZHANG Z, CHEN H, et al. Temporal variability profiling of the default mode across epilepsy subtypes[J]. Epilepsia, 2021, 62(1): 61-73. DOI: 10.1111/epi.16759.
[10]
FU Z, TU Y, DI X, et al. Transient increased thalamic-sensory connectivity and decreased whole-brain dynamism in autism[J]. Neuroimage, 2019, 190: 191-204. DOI: 10.1016/j.neuroimage.2018.06.003.
[11]
HAN L, SONG X K, LI C S. Dynamic analysis of epileptic causal brain networks based on directional transfer function[J]. Sheng Wu Yi Xue Gong Cheng Xue Za Zhi, 2022, 39(6): 1082-1088, 1096. DOI: 10.7507/1001-5515.202202022.
[12]
TU Y, FU Z, MAO C, et al. Distinct thalamocortical network dynamics are associated with the pathophysiology of chronic low back pain[J/OL]. Nat Commun, 2020, 11(1): 3948 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/32769984/. DOI: 10.1038/s41467-020-17788-z.
[13]
GONZALEZ-CASTILLO J, BANDETTINI P A. Task-based dynamic functional connectivity: recent findings and open questions[J]. Neuroimage, 2018, 180(Pt B): 526-533. DOI: 10.1016/j.neuroimage.2017.08.006.
[14]
KUNDU S, MING J, STEVENS J. Developing multimodal dynamic functional connectivity as a neuroimaging biomarker[J]. Brain Connect, 2021, 11(7): 529-542. DOI: 10.1089/brain.2020.0900.
[15]
COURTIOL J, GUYE M, BARTOLOMEI F, et al. Dynamical mechanisms of interictal resting-state functional connectivity in epilepsy[J]. J Neurosci, 2020, 40(29): 5572-5588. DOI: 10.1523/JNEUROSCI.0905-19.2020.
[16]
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 Imaging, 2018, 9(8): 579-588. DOI: 10.12015/issn.1674-8034.2018.08.005.
[17]
YANG Y, CHEN D, WANG J, et al. Dynamic evolution of the anterior cingulate-insula network during seizures[J/OL]. CNS Neurosci Ther, 2023 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/37309272/. DOI: 10.1111/cns.14310.
[18]
YAESOUBI M, ALLEN E A, MILLER R L, et al. Dynamic coherence analysis of resting fmri data to jointly capture state-based phase, frequency, and time-domain information[J/OL]. Neuroimage, 2015, 120 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/26162552/. DOI: 10.1016/j.neuroimage.2015.07.002.
[19]
MACKAY M, HUO S, KAISER M. Spatial organisation of the mesoscale connectome: a feature influencing synchrony and metastability of network dynamics[J/OL]. PLoS Comput Biol, 2023, 19(8): e1011349 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/37552650/. DOI: 10.1371/journal.pcbi.1011349.
[20]
MOOSAVI S A, TRUCCOLO W. Criticality in probabilistic models of spreading dynamics in brain networks: epileptic seizures[J/OL]. PLoS Comput Biol, 2023, 19(2): e1010852 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/36749796/. DOI: 10.1371/journal.pcbi.1010852.
[21]
XIE H, ZHENG C Y, HANDWERKER D A, et al. Efficacy of different dynamic functional connectivity methods to capture cognitively relevant information[J]. Neuroimage, 2019, 188: 502-514. DOI: 10.1016/j.neuroimage.2018.12.037.
[22]
JAFARIAN A, ZEIDMAN P, WYKES R C, et al. Adiabatic dynamic causal modelling[J/OL]. Neuroimage, 2021, 238: 118243 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/34116151/. DOI: 10.1016/j.neuroimage.2021.118243.
[23]
ALONSO S, TYBOROWSKA A, IKANI N, et al. Depression recurrence is accompanied by longer periods in default mode and more frequent attentional and reward processing dynamic brain-states during resting-state activity[J]. Hum Brain Mapp, 2023, 44(17): 5770-5783. DOI: 10.1002/hbm.26475.
[24]
WANG C, YANG L, LIN Y, 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 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/36743477/. DOI: 10.3389/fnint.2022.922577.
[25]
KOTTARAM A, JOHNSTON L A, COCCHI L, et al. Brain network dynamics in schizophrenia: reduced dynamism of the default mode network[J]. Hum Brain Mapp, 2019, 40(7): 2212-2228. DOI: 10.1002/hbm.24519.
[26]
BATISTA TSUKAHARA V H, DE OLIVEIRA JÚNIOR J N, DE OLIVEIRA BARTH V B, et al. Data-driven network dynamical model of rat brains during acute ictogenesis[J/OL]. Front Neural Circuits, 2022, 16: 747910 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/36034337/. DOI: 10.3389/fncir.2022.747910.
[27]
WARNICK R, GUINDANI M, ERHARDT E, et al. A bayesian approach for estimating dynamic functional network connectivity in fmri data[J]. J Am Stat Assoc, 2018, 113(521): 134-151. DOI: 10.1080/01621459.2017.1379404.
[28]
LI Y, WANG J, WANG X, et al. Reconfiguration of static and dynamic thalamo-cortical network functional connectivity of epileptic children with generalized tonic-clonic seizures[J/OL]. Front Neurosci, 2022, 16: 953356 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/35937891/. DOI: 10.3389/fnins.2022.953356.
[29]
PATIL A U, GHATE S, MADATHIL D, et al. Static and dynamic functional connectivity supports the configuration of brain networks associated with creative cognition: 1[J/OL]. Sci Rep, 2021, 11(1): 165 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/33420212/. DOI: 10.1038/s41598-020-80293-2.
[30]
LIU G, ZHENG W, LIU H, et al. Aberrant dynamic structure-function relationship of rich-club organization in treatment-naïve newly diagnosed juvenile myoclonic epilepsy[J]. Hum Brain Mapp, 2022, 43(12): 3633-3645. DOI: 10.1002/hbm.25873.
[31]
ACHARYA U R, OH S L, HAGIWARA Y, et al. Deep convolutional neural network for the automated detection and diagnosis of seizure using eeg signals[J]. Comput Biol Med, 2018, 100: 270-278. DOI: 10.1016/j.compbiomed.2017.09.017.
[32]
JIANG S, LI H, PEI H, et al. Connective profiles and antagonism between dynamic and static connectivity underlying generalized epilepsy[J]. Brain Struct Funct, 2021, 226(5): 1423-1435. DOI: 10.1007/s00429-021-02248-1.
[33]
JIANG S, LI H, LIU L, et al. Voxel-wise functional connectivity of the default mode network in epilepsies: a systematic review and meta-analysis[J]. Curr Neuropharmacol, 2022, 20(1): 254-266. DOI: 10.2174/1570159X19666210325130624.
[34]
WANG Y, LI Y, SUN F, et al. Altered neuromagnetic activity in default mode network in childhood absence epilepsy[J/OL]. Front Neurosci, 2023, 17: 1133064 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/37008207/. DOI: 10.3389/fnins.2023.1133064.
[35]
GONZÁLEZ H F J, NARASIMHAN S, GOODALE S E, et al. Arousal and salience network connectivity alterations in surgical temporal lobe epilepsy[J]. J Neurosurg, 2023, 138(3): 810-820. DOI: 10.3171/2022.5.JNS22837.
[36]
OLIVEIRA-SILVA P, MAIA L, COUTINHO J, et al. Nodes of the default mode network implicated in the quality of empathic responses: a clinical perspective of the empathic response[J/OL]. Int J Clin Health Psychol, 2023, 23(1): 100319 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/36168601/. DOI: 10.1016/j.ijchp.2022.100319.
[37]
YANG T, REN J, ZHANG Y, et al. Pretreatment topological disruptions of whole-brain networks exist in childhood absence epilepsy: a resting-state eeg-fmri study[J/OL]. Epilepsy Res, 2022, 182: 106909 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/35339064/. DOI: 10.1016/j.eplepsyres.2022.106909.
[38]
QIN Y, LI S, YAO D, et al. Causality analysis to the abnormal subcortical-cortical connections in idiopathic-generalized epilepsy[J/OL]. Front Neurosci, 2022, 16: 925968 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/35844218/. DOI: 10.3389/fnins.2022.925968.
[39]
GOTMAN J, GROVA C, BAGSHAW A, et al. Generalized epileptic discharges show thalamocortical activation and suspension of the default state of the brain[J]. Proc Natl Acad Sci U S A, 2005, 102(42): 15236-15240. DOI: 10.1073/pnas.0504935102.
[40]
WARSI N M, YAN H, SURESH H, et al. The anterior and centromedian thalamus: anatomy, function, and dysfunction in epilepsy[J/OL]. Epilepsy Res, 2022, 182: 106913 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/35395570/. DOI: 10.1016/j.eplepsyres.2022.106913.
[41]
BURDETTE D E, HAYKAL M A, JAROSIEWICZ B, et al. Brain-responsive corticothalamic stimulation in the centromedian nucleus for the treatment of regional neocortical epilepsy[J/OL]. Epilepsy Behav, 2020, 112: 107354 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/32919199/. DOI: 10.1016/j.yebeh.2020.107354.
[42]
BERÉNYI A, BELLUSCIO M, MAO D, et al. Closed-loop control of epilepsy by transcranial electrical stimulation[J]. Science, 2012, 337(6095): 735-737. DOI: 10.1126/science.1223154.
[43]
LIAO W, ZHANG Z, MANTINI D, et al. Dynamical intrinsic functional architecture of the brain during absence seizures[J]. Brain Struct Funct, 2014, 219(6): 2001-2015. DOI: 10.1007/s00429-013-0619-2.
[44]
JIANG S, PEI H, HUANG Y, et al. Dynamic temporospatial patterns of functional connectivity and alterations in idiopathic generalized epilepsy[J/OL]. Int J Neural Syst, 2020, 30(12): 2050065 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/33161788/. DOI: 10.1142/S0129065720500653.
[45]
LIU F, WANG Y, LI M, et al. Dynamic functional network connectivity in idiopathic generalized epilepsy with generalized tonic-clonic seizure[J]. Hum Brain Mapp, 2017, 38(2): 957-973. DOI: 10.1002/hbm.23430.
[46]
YANG T, ZHANG Y, ZHANG T, et al. Altered dynamic functional connectivity of striatal-cortical circuits in juvenile myoclonic epilepsy[J]. Seizure, 2022, 101: 103-108. DOI: 10.1016/j.seizure.2022.07.002.
[47]
VAUDANO A E, LAUFS H, KIEBEL S J, et al. Causal hierarchy within the thalamo-cortical network in spike and wave discharges[J/OL]. PLoS One, 2009, 4(8): e6475 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/19649252/. DOI: 10.1371/journal.pone.0006475.
[48]
QIN Y, JIANG S, ZHANG Q, et al. BOLD-fmri activity informed by network variation of scalp eeg in juvenile myoclonic epilepsy[J/OL]. Neuroimage Clin, 2019, 22: 101759 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/30897433/. DOI: 10.1016/j.nicl.2019.101759.
[49]
WILKE C, DING L, HE B. An adaptive directed transfer function approach for detecting dynamic causal interactions[J]. Annu Int Conf IEEE Eng Med Biol Soc, 2007, 2007: 4949-4952. DOI: 10.1109/IEMBS.2007.4353451.
[50]
VATAMAN A, CIOLAC D, CHIOSA V, et al. Dynamic flexibility and controllability of network communities in juvenile myoclonic epilepsy[J/OL]. Neurobiol Dis, 2023, 179: 106055 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/36849015/. DOI: 10.1016/j.nbd.2023.106055.
[51]
SNYDER A D, MA L, STEINBERG J L, et al. Dynamic causal modeling self-connectivity findings in the functional magnetic resonance imaging neuropsychiatric literature[J/OL]. Front Neurosci, 2021, 15: 636273 [2023-08-16]. https://pubmed.ncbi.nlm.nih.gov/34456665/. DOI: 10.3389/fnins.2021.636273.

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