Power spectral density characteristics in EEG of infantile epileptic spasms syndrome_Journal of Epilepsy

Authors：

CHENG Weike , NIU Yue , XU Zhao ,  YANG Zhixian

Department of Pediatrics, Peking University People's Hospital, Beijing 100044, China;

Corresponding author：

YANG Zhixian, Email: zhixian.yang@163.com

Keywords：

Infantile epileptic spasms syndrome; Power spectral density; Hypsarrhythmia; Brain function; Spectral entropy

DOI：

10.7507/2096-0247.202505001

Video：

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Objective To compare and analyze the electroencephalographic (EEG) characteristics of infants with infantile epileptic spasms syndrome (IESS) and healthy infants during sleep using power spectral density (PSD) analysis. Methods Infants aged 5 to 9 months with IESS were included, along with an equal number of age-matched healthy controls. EEG signals during sleep were recorded using the Nihon Kohden EEG-1200C system. The energy distribution in the theta (θ), alpha (α), sigma (σ), and beta (β) frequency bands, as well as the morphology and values of PSD within the 4 ~ 30 Hz range, were analyzed. Additionally, spectral entropy (SpEn) was calculated to evaluate signal complexity. Results A total of 10 IESS patients and 10 healthy infants were included. There were no significant differences in gender or age between the two groups (P=0.64, P=0.88). In both groups, PSD values showed a linear decreasing trend with increasing frequency. However, the IESS group showed notable differences in PSD morphology, amplitude, and energy distribution compared to controls. These included the absence of a σ-band peak, greater PSD dispersion across electrodes, significant alterations in energy distribution across θ, α, σ, and β bands, and significantly higher PSD values in the 4 ~ 30 Hz range (P<0.000 1). SpEn analysis revealed significantly elevated spectral entropy across the sigma band in the IESS group, indicating a lack of dominant frequencies, increased complexity, reduced rhythmicity, and enhanced disorder. In contrast, healthy controls exhibited elevated SpEn in the alpha band, reflecting the physiological reduction or disappearance of dominant alpha rhythms during sleep. Conclusion Infants with IESS demonstrate distinct EEG characteristics in both PSD and SpEn analyses compared to healthy infants. These quantitative spectral features reflect the underlying abnormalities of EEG in IESS and provide objective insights that complement conventional visual assessment, offering a novel perspective for early diagnosis and therapeutic monitoring.

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18.	Uchida S, Maloney T, Feinberg I. Sigma (12-16 Hz) and beta (20-28 Hz) EEG discriminate NREM and REM sleep. Brain Res, 1994, 659(1-2): 243-248.
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28.	Deboer T. Brain temperature dependent changes in the electroencephalogram power spectrum of humans and animals. J Sleep Res, 1998, 7(4): 254-262.
29.	Sarnthein J, Stern J, Aufenberg C, et al. Increased EEG power and slowed dominant frequency in patients with neurogenic pain. Brain, 2006, 129(1): 55-64.
30.	Newson JJ, Thiagarajan TC. EEG frequency bands in psychiatric disorders: a review of resting state studies. Front Hum Neurosci, 2019, 12: 521.
31.	Nair A, Ewusie J, Pentz R, et al. Mean global field power is reduced in infantile epileptic spasms syndrome after response to vigabatrin. Front Neurol, 2024, 15: 1476476.

1. Jia JL, Chen S, Sivarajah V, et al. Latitudinal differences on the global epidemiology of infantile spasms: systematic review and meta-analysis. Orphanet J Rare Dis, 2018, 13: 1-17.
2. Baba S, Okanishi T, Homma Y, et al. Efficacy of long‐term adrenocorticotropic hormone therapy for West syndrome: a retrospective multicenter case series. Epilepsia Open, 2021, 6(2): 402-412.
3. Takeuchi H, Kikuchi K, Takeda R, et al. Effectiveness of vigabatrin for infantile epileptic spasm syndrome categorized by etiologies. Seizure, 2024, 122: 113-118.
4. Pellock JM, Hrachovy R, Shinnar S, et al. Infantile spasms: a US consensus report. Epilepsia, 2010, 51(10): 2175-2189.
5. 孙于林, 陈健, 杨光, 脑电图评分在婴儿痉挛症的应用进展. 中华实用儿科临床杂志, 2021, 36(10) : 794-797.
6. 阮卫云, 郅艳华, 郭燕燕. 婴儿痉挛症的脑电图表现及与ACTH疗效的相关性. 江西医药, 2023, 58(4): 444-445,448.
7. 王江涛, 曲歌, 梁建民, 等. 150例婴儿痉挛发作期及发作间期动态脑电图分析. 中国当代儿科杂志, 2013, 15(9): 779-781.
8. Fernandez LMJ, Lüthi A. Sleep spindles: mechanisms and functions. Physiol Rev, 2020, 100(2): 805-868.
9. Auvin S. Paediatric epilepsy and cognition. Dev Med Child Neurol, 2022, 64(12): 1444-1452.
10. Cragg L, Kovacevic N, McIntosh AR, et al. Maturation of EEG power spectra in early adolescence: a longitudinal study. Dev Sci, 2011, 14(5): 935-943.
11. Beste C, Münchau A, Frings C. Towards a systematization of brain oscillatory activity in actions. Commun Biol, 2023, 6(1): 137.
12. Tawhid MNA, Siuly S, Kabir E, et al. Exploring frequency band-based biomarkers of EEG signals for mild cognitive impairment detection. IEEE Trans Neural Syst Rehabil Eng, 2023, 32: 189-199.
13. Ismail LE, Karwowski W. Applications of EEG indices for the quantification of human cognitive performance: a systematic review and bibliometric analysis. PLoS One, 2020, 15(12): e0242857.
14. Wojcik GM, Masiak J, Kawiak A, et al. Mapping the human brain in frequency band analysis of brain cortex electroencephalographic activity for selected psychiatric disorders. Front Neuroinform, 2018, 12: 73.
15. Perez V, Duque A, Hidalgo V, et al. EEG frequency bands in subjective cognitive decline: a systematic review of resting state studies. Biol Psychol, 2024: 108823.
16. Ünsal E, Duygun R, Yemeniciler İ, et al. From infancy to childhood: a comprehensive review of event-and task-related brain oscillations. Brain Sci, 2024, 14(8): 837.
17. Purcell SM, Manoach D S, Demanuele C, et al. Characterizing sleep spindles in 11, 630 individuals from the National Sleep Research Resource. Nature communications, 2017, 8(1): 15930.
18. Uchida S, Maloney T, Feinberg I. Sigma (12-16 Hz) and beta (20-28 Hz) EEG discriminate NREM and REM sleep. Brain Res, 1994, 659(1-2): 243-248.
19. Nicolas J, King B R, Levesque D, et al. Sigma oscillations protect or reinstate motor memory depending on their temporal coordination with slow waves. Elife, 2022, 11: e73930.
20. Petzka M, Chatburn A, Charest I, et al. Sleep spindles track cortical learning patterns for memory consolidation. Curr Biol, 2022, 32(11): 2349-2356.
21. Satomaa AL, Mäkelä T, Saarenpää-Heikkilä O, et al. Slow-wave activity and sigma activities are associated with psychomotor development at 8 months of age. Sleep, 2020, 43(9): zsaa061.
22. Smith RJ, Hu DK, Shrey DW, et al. Computational characteristics of interictal EEG as objective markers of epileptic spasms. Epilepsy Res, 2021, 176: 106704.
23. Dimitrov T, He M, Stickgold R, et al. Sleep spindles comprise a subset of a broader class of electroencephalogram events. Sleep, 2021, 44(9): zsab099.
24. Fernandez LMJ, Lüthi A. Sleep spindles: mechanisms and functions. Physiol Rev, 2020, 34: 00678.
25. De Gennaro L, Ferrara M. Sleep spindles: an overview. Sleep Med Rev, 2003, 7(5): 423-440.
26. Petroff OA, Spencer DD, Goncharova II, et al. A comparison of the power spectral density of scalp EEG and subjacent electrocorticograms. Clin Neurophysiol, 2016, 127(2): 1108-1112.
27. Grin-Yatsenko VA, Baas I, Ponomarev VA, et al. EEG power spectra at early stages of depressive disorders. J Clin Neurophysiol, 2009, 26(6): 401-406.
28. Deboer T. Brain temperature dependent changes in the electroencephalogram power spectrum of humans and animals. J Sleep Res, 1998, 7(4): 254-262.
29. Sarnthein J, Stern J, Aufenberg C, et al. Increased EEG power and slowed dominant frequency in patients with neurogenic pain. Brain, 2006, 129(1): 55-64.
30. Newson JJ, Thiagarajan TC. EEG frequency bands in psychiatric disorders: a review of resting state studies. Front Hum Neurosci, 2019, 12: 521.
31. Nair A, Ewusie J, Pentz R, et al. Mean global field power is reduced in infantile epileptic spasms syndrome after response to vigabatrin. Front Neurol, 2024, 15: 1476476.

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