Share this content in WeChat
Original Article
Uncoupling between functional connectivity density and amplitude of low frequency fluctuation in childhood absence epilepsy
YU Qianqian  LIU Gaoping  XU Qiang  ZHANG Qirui  LU Guangming  ZHANG Zhiqiang 

Cite this article as: Yu QQ, Liu GP, Xu Q, et al. Uncoupling between functional connectivity density and amplitude of low frequency fluctuation in childhood absence epilepsy[J]. Chin J Magn Reson Imaging, 2022, 13(7): 75-79, 89. DOI:10.12015/issn.1674-8034.2022.07.013.

[Abstract] Objective To observe the changes of amplitude of low frequency fluctuation (ALFF) and functional connectivity density (FCD) in childhood absence epilepsy (CAE), which would assist to elucidate the its clinical and pathophysiological mechanism.Materials and Methods Thirty-seven CAE patients and fifty age-and sex-matched healthy controls underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning, the clinical data were collected. The whole brain mappings of ALFF, FCD and ALFF-FCD were calculated and two-sample t-tests were employed to detect significant differences of these index. Across-voxel correlation analysis was used to calculate the correlation between the brain areas with significant differences for ALFF, FCD and ALFF-FCD. Additionally, correlation analysis was performed between these index and the duration of the disease in CAE patients.Results Compared with the control group, the CAE group showed a reverse change pattern of ALFF and FCD in specific brain areas: the increased ALFF and decreased FCD in bilateral thalamus, while the ALFF of default mode network such as precuneus and bilateral inferior parietal lobules decreased and the FCD increased (GRF correction, voxel-P<0.01, cluster-P<0.05). Correlation analysis revealed that in CAE, the correlation coefficient of ALFF and FCD in thalamus (r=0.374, P=0.022) decreased compared with control group (r=0.448, P=0.001), and there was a significant difference (t=-2.095, P=0.020); In addition, the index of amplitude subtracting connectivity (ALFF-FCD value) in thalamus was negatively correlated with the duration of disease (r=-0.473, P<0.001).Conclusions The thalamus and default mode brain regions showed significant functional changes by different rs-fMRI indexes, reflecting that they are important brain regions involved in the pathophysiological mechanism of childhood absence epilepsy.
[Keywords] childhood absence epilepsy;amplitude of low frequency fluctuation;functional connection density;uncoupling;resting-state functional magnetic resonance imaging

YU Qianqian   LIU Gaoping   XU Qiang   ZHANG Qirui   LU Guangming   ZHANG Zhiqiang*  

Department of Diagnostic Radiology, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China

Zhang ZQ, E-mail:

Conflicts of interest   None.

Received  2021-10-14
Accepted  2022-03-07
DOI: 10.12015/issn.1674-8034.2022.07.013
Cite this article as: Yu QQ, Liu GP, Xu Q, et al. Uncoupling between functional connectivity density and amplitude of low frequency fluctuation in childhood absence epilepsy[J]. Chin J Magn Reson Imaging, 2022, 13(7): 75-79, 89.DOI:10.12015/issn.1674-8034.2022.07.013

Falco-Walter JJ, Scheffer IE, Fisher RS. The new definition and classification of seizures and epilepsy[J]. Epilepsy Res, 2018, 139: 73-79. DOI: 10.1016/j.eplepsyres.2017.11.015.
Crunelli V, Lőrincz ML, McCafferty C, et al. Clinical and experimental insight into pathophysiology, comorbidity and therapy of absence seizures[J]. Brain, 2020, 143(8): 2341-2368. DOI: 10.1093/brain/awaa072.
Sysoeva MV, Lüttjohann A, van Luijtelaar G, et al. Dynamics of directional coupling underlying spike-wave discharges[J]. Neuroscience, 2016, 314: 75-89. DOI: 10.1016/j.neuroscience.2015.11.044.
Shu MZ, Yu CY, Shi Q, et al. Alterations in white matter integrity and asymmetry in patients with benign childhood epilepsy with centrotemporal spikes and childhood absence epilepsy: an automated fiber quantification tractography study[J]. Epilepsy Behav, 2021, 123: 108235. DOI: 10.1016/j.yebeh.2021.108235.
Fojtiková D, Brázdil M, Horký J, et al. Magnetic resonance spectroscopy of the thalamus in patients with typical absence epilepsy[J]. Seizure, 2006, 15(7): 533-540. DOI: 10.1016/j.seizure.2006.06.007.
Guo JN, Kim R, Chen Y, et al. Impaired consciousness in patients with absence seizures investigated by functional MRI, EEG, and behavioural measures: a cross-sectional study[J]. Lancet Neurol, 2016, 15(13): 1336-1345. DOI: 10.1016/S1474-4422(16)30295-2.
Barkhof F, Haller S, Rombouts SARB. Resting-state functional MR imaging: a new window to the brain[J]. Radiology, 2014, 272(1): 29-49. DOI: 10.1148/radiol.14132388.
Edlow BL, Claassen J, Schiff ND, et al. Recovery from disorders of consciousness: mechanisms, prognosis and emerging therapies[J]. Nat Rev Neurol, 2021, 17(3): 135-156. DOI: 10.1038/s41582-020-00428-x.
Yan YB, Xie GH, Zhou HY, et al. Altered spontaneous brain activity in patients with childhood absence epilepsy: associations with treatment effects[J]. Neuroreport, 2020, 31(8): 613-618. DOI: 10.1097/WNR.0000000000001447.
Yan CG, Yang Z, Colcombe SJ, et al. Concordance among indices of intrinsic brain function: insights from inter-individual variation and temporal dynamics[J]. Sci Bull, 2017, 62(23): 1572-1584. DOI: 10.1016/j.scib.2017.09.015.
Buckner RL, DiNicola LM. The brain's default network: updated anatomy, physiology and evolving insights[J]. Nat Rev Neurosci, 2019, 20(10): 593-608. DOI: 10.1038/s41583-019-0212-7.
Zhang ZQ, Xu Q, Liao W, et al. Pathological uncoupling between amplitude and connectivity of brain fluctuations in epilepsy[J]. Hum Brain Mapp, 2015, 36(7): 2756-2766. DOI: 10.1002/hbm.22805.
Garrett DD, Epp SM, Perry A, et al. Local temporal variability reflects functional integration in the human brain[J]. Neuroimage, 2018, 183: 776-787. DOI: 10.1016/j.neuroimage.2018.08.019.
Goris RLT, Movshon JA, Simoncelli EP. Partitioning neuronal variability[J]. Nat Neurosci, 2014, 17(6): 858-865. DOI: 10.1038/nn.3711.
Deng SW, Franklin CG, O'Boyle M, et al. Hemodynamic and metabolic correspondence of resting-state voxel-based physiological metrics in healthy adults[J]. NeuroImage, 2022, 250: 118923. DOI: 10.1016/j.neuroimage.2022.118923.
Zhang ZQ, Xu Q, Lu GM, et al. Dynamic functional MRI study of absence seizures[J]. Chin J Magn Reson Imaging, 2013, 4(1): 3-7. DOI: 10.3969/j.issn.1674-8034.2013.01.002.
Perani S, Tierney TM, Centeno M, et al. Thalamic volume reduction in drug-naive patients with new-onset genetic generalized epilepsy[J]. Epilepsia, 2018, 59(1): 226-234. DOI: 10.1111/epi.13955.
Wang XY, Fang P, Jiao DM, et al. Topological organization alterations of whole-brain functional networks in patients with childhood absence epilepsy: associations with treatment effects[J]. Dis Markers, 2021, 2021: 2727596. DOI: 10.1155/2021/2727596.
Zhang H, Qian ZY, Lu GM, et al. Investigation of childhood absence seizures based on EEG correlated fMRI technology[J]. Acta Biophys Sin, 2011, 27(2): 167-174.
Yang TH, Fang ZJ, Ren JC, et al. Altered spontaneous activity in treatment-naive childhood absence epilepsy revealed by Regional Homogeneity[J]. J Neurol Sci, 2014, 340(1/2): 58-62. DOI: 10.1016/j.jns.2014.02.025.
Qiu WC, Wang XS. Structural abnormalities of default mode network in childhood absence epilepsy revealed by diffusion tensor imaging[J]. J Epilepsy, 2017, 3(3): 187-192. DOI: 10.7507/2096-0247.20170028.
Li YW, Wang EF, Han X, et al. Default mode network in childhood absence epilepsy by 3.0T magnetic resonance imaging[J]. Natl Med J China, 2014, 1(45): 3540-3544. DOI: 10.3760/cma.j.issn.0376-2491.2014.45.002.
Wainio-Theberge S, Wolff A, Northoff G. Dynamic relationships between spontaneous and evoked electrophysiological activity[J]. Commun Biol, 2021, 4(1): 741. DOI: 10.1038/s42003-021-02240-9.
Moreau JT, Saint-Martin C, Baillet S, et al. MNI SISCOM: an open-source tool for computing subtraction ictal single-photon emission CT coregistered to MRI[J]. J Digit Imaging, 2021, 34(2): 357-361. DOI: 10.1007/s10278-021-00422-9.

PREV Development and assessment of a novel nomogram based on multiple parameters MRI for predicting the risk of reintervention after high intensity focused ultrasound treatment of uterine leiomyoma
NEXT Preliminary study on brain network of patients with somatic symptom disorder based on probabilistic fiber tracking

Tel & Fax: +8610-67113815    E-mail: