Abstract Objective To investigate the role of brain functional connectivity and nonlinear dynamic analysis in brain function assessment for infants with controlled infantile spasm (IS). Methods A retrospective analysis was performed on 14 children with controlled IS (IS group) who were admitted to the Department of Neurology, Anhui Provincial Children's Hospital, from January 2019 to January 2023. Twelve healthy children, matched for sex and age, were enrolled as the control group. Electroencephalogram (EEG) data were analyzed for both groups to compare the features of brain network, and nonlinear dynamic indicators were calculated, including approximate entropy, sample entropy, permutation entropy, and permutation Lempel-Ziv complexity. Results Brain functional connectivity showed that compared with the control group, the IS group had an increase in the strength of functional connectivity, and there was a significant difference between the two groups in the connection strength between the Fp2 and F8 channels (P<0.05). The network stability analysis showed that the IS group had a significantly higher network stability than the control group at different time windows (P<0.05). The nonlinear dynamic analysis showed that compared with the control group, the IS group had a significantly lower sample entropy of Fz electrode (P<0.05). Conclusions Abnormalities in brain network and sample entropy may be observed in some children with controlled IS, and it is suggested that quantitative EEG analysis parameters can serve as neurological biomarkers for evaluating brain function in children with IS.
YE Xiao-Fei,HU Pan-Pan,YANG Yang et al. Application of brain functional connectivity and nonlinear dynamic analysis in brain function assessment for infants with controlled infantile spasm[J]. CJCP, 2023, 25(10): 1040-1045.
YE Xiao-Fei,HU Pan-Pan,YANG Yang et al. Application of brain functional connectivity and nonlinear dynamic analysis in brain function assessment for infants with controlled infantile spasm[J]. CJCP, 2023, 25(10): 1040-1045.
Specchio N, Wirrell EC, Scheffer IE, et al. International League Against Epilepsy classification and definition of epilepsy syndromes with onset in childhood: position paper by the ILAE Task Force on Nosology and Definitions[J]. Epilepsia, 2022, 63(6): 1398-1442. PMID: 35503717. DOI: 10.1111/epi.17241.
Mandelbaum DE, Krawciw N, Assing E, et al. Topographic mapping of brain potentials in the newborn infant: the establishment of normal values and utility in assessing infants with neurological injury[J]. Acta Paediatr, 2000, 89(9): 1104-1110. PMID: 11071093. DOI: 10.1080/713794558.
Shrey DW, Kim McManus O, Rajaraman R, et al. Strength and stability of EEG functional connectivity predict treatment response in infants with epileptic spasms[J]. Clin Neurophysiol, 2018, 129(10): 2137-2148. PMID: 30114662. PMCID: PMC6193760. DOI: 10.1016/j.clinph.2018.07.017.
Pavone P, Striano P, Falsaperla R, et al. Infantile spasms syndrome, West syndrome and related phenotypes: what we know in 2013[J]. Brain Dev, 2014, 36(9): 739-751. PMID: 24268986. DOI: 10.1016/j.braindev.2013.10.008.
Gaily E, Appelqvist K, Kantola-Sorsa E, et al. Cognitive deficits after cryptogenic infantile spasms with benign seizure evolution[J]. Dev Med Child Neurol, 1999, 41(10): 660-664. PMID: 10587041. DOI: 10.1017/s001216229900136x.
Sunwoo JS, Cha KS, Byun JI, et al. Abnormal activation of motor cortical network during phasic REM sleep in idiopathic REM sleep behavior disorder[J]. Sleep, 2019, 42(2): zsy227. PMID: 30445515. DOI: 10.1093/sleep/zsy227.
Wang W, Li H, Yan J, et al. Automatic detection of interictal ripples on scalp EEG to evaluate the effect and prognosis of ACTH therapy in patients with infantile spasms[J]. Epilepsia, 2021, 62(9): 2240-2251. PMID: 34309835. DOI: 10.1111/epi.17018.
Tedrus GM, Negreiros LM, Ballarim RS, et al. Correlations between cognitive aspects and quantitative EEG in adults with epilepsy[J]. Clin EEG Neurosci, 2019, 50(5): 348-353. PMID: 30198328. DOI: 10.1177/1550059418793553.
Chen X, Yan CG. Hypostability in the default mode network and hyperstability in the frontoparietal control network of dynamic functional architecture during rumination[J]. Neuroimage, 2021, 241: 118427. PMID: 34311069. DOI: 10.1016/j.neuroimage.2021.118427.
Puglia MP, Li D, Leis AM, et al. Neurophysiologic complexity in children increases with developmental age and is reduced by general anesthesia[J]. Anesthesiology, 2021, 135(5): 813-828. PMID: 34491305. DOI: 10.1097/ALN.0000000000003929.