A study on the propagation characteristics of epileptic spike signals based on simultaneous intracranial and scalp electroencephalography_Journal of Biomedical Engineering

Authors：

JIANG Mingming ¹ , GAO Dandan ² ,  LI Chunsheng ¹

1. Department of Biomedical Engineering, School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, P. R. China;
2. Department of Neurosurgery, General Hospital of Northern Theater Command, Shenyang 110016, P. R. China;

Corresponding?author：

LI Chunsheng, Email: lichunsheng@sut.edu.cn

Keywords：

Spike; Epilepsy; Simultaneous electroencephalography; Neuroelectrophysiological characteristics

DOI：

10.7507/1001-5515.202602025

Video：

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Abstract Full text Figures/Tables Video References Cited by

Spikes, as a key electrophysiological marker of abnormal synchronized neuronal discharges, can be identified and detected by scalp electroencephalography (EEG), and are of great value for localizing epileptic foci and investigating the mechanisms of epilepsy. However, spike propagation is strongly influenced by the skull, making it difficult to infer the precise intracranial origin of spikes from scalp EEG alone. Therefore, based on simultaneous intracranial and scalp EEG recordings, this study investigated the propagation characteristics of spikes from the intracranial space to the scalp. The study mainly focused on four aspects: the characteristics of simultaneous intracranial and scalp spikes, the scalp visibility of intracranial spikes, the spatial distribution of scalp spikes, and the influence of epileptogenic and non-epileptogenic regions on spike propagation. The results showed that spikes detectable on the scalp differed significantly in energy-related features from those not detectable on the scalp ［MD = 2.6 × 10^?6 (2.5 × 10^?6, 2.6 × 10^?6), P < 0.01］. When the intracranial spike activation area was less than 10 cm², the scalp detection rate was 18.9%; when the area reached 30～40 cm², the detection rate increased to 62.5%, showing an increasing trend. After spikes propagated to the scalp, the detection rate decreased by 63.5% when the horizontal distance of their spatial distribution exceeded 4 cm. In addition, there was no statistically significant difference in scalp detection rate between spikes originating from epileptogenic and non-epileptogenic regions (P > 0.05). In summary, these findings are important for elucidating the propagation characteristics of spikes and may provide quantitative evidence for electrophysiological analysis and focus localization in epilepsy.

Citation： JIANG Mingming, GAO Dandan, LI Chunsheng. A study on the propagation characteristics of epileptic spike signals based on simultaneous intracranial and scalp electroencephalography. Journal of Biomedical Engineering, 2026, 43(4): 704-710. doi: 10.7507/1001-5515.202602025 Copy

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2.	Fisher R S, Acevedo C, Arzimanoglou A, et al. ILAE official report: a practical clinical definition of epilepsy[J]. Epilepsia, 2014, 55(4): 475-482.
3.	Brodie M J, Barry S J E, Bamagous G A, et al. Patterns of treatment response in newly diagnosed epilepsy[J]. Neurology, 2012, 78(20): 1548-1554.
4.	Wang Z, Wu D, Dong F, et al. A novel spike detection algorithm based on multi-channel of BECT EEG signals[J]. IEEE Trans Circuits Syst II Express Briefs, 2020, 67(12): 3592-3596.
5.	潘佳麗, 王靜, 閆兆芬, 等. 發笑性癲癇發作的臨床及腦電圖特征與致癇區定位[J]. 癲癇雜志, 2025, 11(3): 185-195.
6.	尹寧, 賈哲沛, 王樂, 等. 基于立體定向腦電圖的致癇區神經脆弱性分析[J]. 生物醫學工程學雜志, 2023, 40(5): 837-842.
7.	Staley K J, Dudek F E. Interictal spikes and epileptogenesis[J]. Epilepsy Curr, 2006, 6(6): 199-202.
8.	Rosenow F, Lüders H. Presurgical evaluation of epilepsy[J]. Brain, 2001, 124(9): 1683-1700.
9.	Yang D, Ma R, Yang N, et al. Repeated long sessions of transcranial direct current stimulation reduces seizure frequency in patients with refractory focal epilepsy: an open-label extension study[J]. Epilepsy Behav, 2022, 135: 108876.
10.	Lin L C, Ouyang C S, Chiang C T, et al. Cumulative effect of transcranial direct current stimulation in patients with partial refractory epilepsy and its association with phase lag index-a preliminary study[J]. Epilepsy Behav, 2018, 84: 142-147.
11.	劉揚, 李春勝, 韓雨軒. 融合頭皮腦電圖與神經計算模型的癲癇經顱電刺激靶區定位研究[J]. 生物醫學工程學雜志, 2025, 42(6): 1123-1130.
12.	Frauscher B, Mansilla D, Abdallah C, et al. Learn how to interpret and use intracranial EEG findings[J]. Epileptic Disord, 2024, 26(1): 1-59.
13.	Ebersole J S. EEG source imaging in presurgical evaluations[J]. J Clin Neurophysiol, 2024, 41(1): 36-49.
14.	Thio B J, Sinha N, Davis K A, et al. Stereo-EEG propagating source reconstruction identifies new surgical targets for epilepsy patients[J]. Brain, 2025, 148(3): 764-775.
15.	Matarrese M A G, Loppini A, Fabbri L, et al. Spike propagation mapping reveals effective connectivity and predicts surgical outcome in epilepsy[J]. Brain, 2023, 146(9): 3898-3912.
16.	Tatum W O, Rubboli G, Kaplan P W, et al. Clinical utility of EEG in diagnosing and monitoring epilepsy in adults[J]. Clin Neurophysiol, 2018, 129(5): 1056-1082.
17.	Jiang L, Liang Y, Genon S, et al. Spatial-rhythmic network as a biomarker of familial risk for psychotic bipolar disorder[J]. Nat Ment Health, 2023, 1(11): 887-899.
18.	張婷, 劉燕, 彭博, 等. 基于囟門補償的嬰兒腦電正問題建模方法[J]. 生物醫學工程學雜志, 2024, 41(6): 1085-1094.
19.	Zhao L, Liu Y, Gao J A, et al. Visual imagery-based brain-computer interaction paradigms and neural encoding and decoding[J]. IEEE Trans Hum Mach Syst, 2025, 55(3): 358-371.
20.	牛瑞奇, 張丞, 吳昌哲, 等. 組織電導率對經顱磁刺激頭模型內電場計算的影響[J]. 生物醫學工程學雜志, 2023, 40(3): 401-408.
21.	Lai Y, van Drongelen W, Ding L, et al. Estimation of in vivo human brain-to-skull conductivity ratio from simultaneous extra- and intracranial electrical potential recordings[J]. Clin Neurophysiol, 2005, 116(2): 456-465.
22.	Tao J X, Ray A, Hawes-Ebersole S, et al. Intracranial EEG substrates of scalp EEG interictal spikes[J]. Epilepsia, 2005, 46(5): 669-676.
23.	Ray A, Tao J X, Hawes-Ebersole S M, et al. Localizing value of scalp EEG spikes: a simultaneous scalp and intracranial study[J]. Clin Neurophysiol, 2007, 118(1): 69-79.
24.	Michel C M, Brunet D. EEG source imaging: a practical review of the analysis steps[J]. Front Neurol, 2019, 10: 325.
25.	Bolzan A, Benoit J, Pizzo F, et al. Correspondence between scalp-EEG and stereoelectroencephalography seizure-onset patterns in patients with MRI-negative drug-resistant focal epilepsy[J]. Epilepsia Open, 2024, 9(2): 568-581.
26.	Jahromi S, Matarrese M A G, Fabbri L, et al. Overlap of spike and ripple propagation onset predicts surgical outcome in epilepsy[J]. Ann Clin Transl Neurol, 2024, 11(10): 2530-2547.
27.	Gulyaev S A. EEG microstate analysis and the EEG inverse problem solution as a tool for diagnosing cognitive dysfunctions in individuals who have had a mild form of COVID-19[J]. Hum Physiol, 2022, 48(5): 587-597.
28.	Casta?o-Candamil S, H?hne J, Martínez-Vargas J D, et al. Solving the EEG inverse problem based on space-time-frequency structured sparsity constraints[J]. NeuroImage, 2015, 118: 598-612.
29.	Frauscher B, Bartolomei F, Kobayashi K, et al. High-frequency oscillations: the state of clinical research[J]. Epilepsia, 2017, 58(8): 1316-1329.
30.	Dimakopoulos V, Gotman J, Klimes P, et al. Multicentre analysis of seizure outcome predicted by removal of high-frequency oscillations[J]. Brain, 2025, 148(5): 1769-1777.
31.	Ye H, Chen C, Weiss S A, et al. Pathological and physiological high-frequency oscillations on electroencephalography in patients with epilepsy[J]. Neurosci Bull, 2024, 40(5): 609-620.
32.	Koessler L, Cecchin T, Colnat-Coulbois S, et al. Catching the invisible: mesial temporal source contribution to simultaneous EEG and SEEG recordings[J]. Brain Topogr, 2015, 28(1): 5-20.
33.	Benoliel T, Arviv O, Doufish D, et al. Depth-to-scalp spatiotemporal dynamics for stereo-EEG[J]. Epilepsy Behav Rep, 2025, 31: 100784.
34.	Cosandier-Rimélé D, Merlet I, Badier J M, et al. The neuronal sources of EEG: modeling of simultaneous scalp and intracerebral recordings in epilepsy[J]. NeuroImage, 2008, 42(1): 135-146.
35.	von Ellenrieder N, Beltrachini L, Perucca P, et al. Size of cortical generators of epileptic interictal events and visibility on scalp EEG[J]. NeuroImage, 2014, 94: 47-54.
36.	Tao J X, Baldwin M, Hawes-Ebersole S, et al. Cortical substrates of scalp EEG epileptiform discharges[J]. J Clin Neurophysiol, 2007, 24(2): 96-100.
37.	Merlet I, Gotman J. Reliability of dipole models of epileptic spikes[J]. Clin Neurophysiol, 1999, 110(6): 1013-1028.
38.	Takenaka M, Pflieger M E, Hori T, et al. Detectability in scalp EEGs of epileptic spikes emitted from brain electrical sources of different sizes and locations: a simulation study using realistic head models of elderly adults[J]. Clin EEG Neurosci, 2025, 56(4): 358-371.
39.	Ramantani G, Dümpelmann M, Koessler L, et al. Simultaneous subdural and scalp EEG correlates of frontal lobe epileptic sources[J]. Epilepsia, 2014, 55(2): 278-288.
40.	Casale M J, Marcuse L V, Young J J, et al. The sensitivity of scalp EEG at detecting seizures—a simultaneous scalp and stereo EEG study[J]. J Clin Neurophysiol, 2022, 39(1): 78-84.
41.	Kramer M A, Ostrowski L M, Song D Y, et al. Scalp recorded spike ripples predict seizure risk in childhood epilepsy better than spikes[J]. Brain, 2019, 142(5): 1296-1309.
42.	Abramovici S, Antony A, Baldwin M E, et al. Features of simultaneous scalp and intracranial EEG that predict localization of ictal onset zone[J]. Clin EEG Neurosci, 2018, 49(3): 206-212.

1. Li C, Sohrabpour A, Jiang H, et al. High-frequency hubs of the ictal cross-frequency coupling network predict surgical outcome in epilepsy patients[J]. IEEE Trans Neural Syst Rehabil Eng, 2021, 29: 1290-1299.
2. Fisher R S, Acevedo C, Arzimanoglou A, et al. ILAE official report: a practical clinical definition of epilepsy[J]. Epilepsia, 2014, 55(4): 475-482.
3. Brodie M J, Barry S J E, Bamagous G A, et al. Patterns of treatment response in newly diagnosed epilepsy[J]. Neurology, 2012, 78(20): 1548-1554.
4. Wang Z, Wu D, Dong F, et al. A novel spike detection algorithm based on multi-channel of BECT EEG signals[J]. IEEE Trans Circuits Syst II Express Briefs, 2020, 67(12): 3592-3596.
5. 潘佳麗, 王靜, 閆兆芬, 等. 發笑性癲癇發作的臨床及腦電圖特征與致癇區定位[J]. 癲癇雜志, 2025, 11(3): 185-195.
6. 尹寧, 賈哲沛, 王樂, 等. 基于立體定向腦電圖的致癇區神經脆弱性分析[J]. 生物醫學工程學雜志, 2023, 40(5): 837-842.
7. Staley K J, Dudek F E. Interictal spikes and epileptogenesis[J]. Epilepsy Curr, 2006, 6(6): 199-202.
8. Rosenow F, Lüders H. Presurgical evaluation of epilepsy[J]. Brain, 2001, 124(9): 1683-1700.
9. Yang D, Ma R, Yang N, et al. Repeated long sessions of transcranial direct current stimulation reduces seizure frequency in patients with refractory focal epilepsy: an open-label extension study[J]. Epilepsy Behav, 2022, 135: 108876.
10. Lin L C, Ouyang C S, Chiang C T, et al. Cumulative effect of transcranial direct current stimulation in patients with partial refractory epilepsy and its association with phase lag index-a preliminary study[J]. Epilepsy Behav, 2018, 84: 142-147.
11. 劉揚, 李春勝, 韓雨軒. 融合頭皮腦電圖與神經計算模型的癲癇經顱電刺激靶區定位研究[J]. 生物醫學工程學雜志, 2025, 42(6): 1123-1130.
12. Frauscher B, Mansilla D, Abdallah C, et al. Learn how to interpret and use intracranial EEG findings[J]. Epileptic Disord, 2024, 26(1): 1-59.
13. Ebersole J S. EEG source imaging in presurgical evaluations[J]. J Clin Neurophysiol, 2024, 41(1): 36-49.
14. Thio B J, Sinha N, Davis K A, et al. Stereo-EEG propagating source reconstruction identifies new surgical targets for epilepsy patients[J]. Brain, 2025, 148(3): 764-775.
15. Matarrese M A G, Loppini A, Fabbri L, et al. Spike propagation mapping reveals effective connectivity and predicts surgical outcome in epilepsy[J]. Brain, 2023, 146(9): 3898-3912.
16. Tatum W O, Rubboli G, Kaplan P W, et al. Clinical utility of EEG in diagnosing and monitoring epilepsy in adults[J]. Clin Neurophysiol, 2018, 129(5): 1056-1082.
17. Jiang L, Liang Y, Genon S, et al. Spatial-rhythmic network as a biomarker of familial risk for psychotic bipolar disorder[J]. Nat Ment Health, 2023, 1(11): 887-899.
18. 張婷, 劉燕, 彭博, 等. 基于囟門補償的嬰兒腦電正問題建模方法[J]. 生物醫學工程學雜志, 2024, 41(6): 1085-1094.
19. Zhao L, Liu Y, Gao J A, et al. Visual imagery-based brain-computer interaction paradigms and neural encoding and decoding[J]. IEEE Trans Hum Mach Syst, 2025, 55(3): 358-371.
20. 牛瑞奇, 張丞, 吳昌哲, 等. 組織電導率對經顱磁刺激頭模型內電場計算的影響[J]. 生物醫學工程學雜志, 2023, 40(3): 401-408.
21. Lai Y, van Drongelen W, Ding L, et al. Estimation of in vivo human brain-to-skull conductivity ratio from simultaneous extra- and intracranial electrical potential recordings[J]. Clin Neurophysiol, 2005, 116(2): 456-465.
22. Tao J X, Ray A, Hawes-Ebersole S, et al. Intracranial EEG substrates of scalp EEG interictal spikes[J]. Epilepsia, 2005, 46(5): 669-676.
23. Ray A, Tao J X, Hawes-Ebersole S M, et al. Localizing value of scalp EEG spikes: a simultaneous scalp and intracranial study[J]. Clin Neurophysiol, 2007, 118(1): 69-79.
24. Michel C M, Brunet D. EEG source imaging: a practical review of the analysis steps[J]. Front Neurol, 2019, 10: 325.
25. Bolzan A, Benoit J, Pizzo F, et al. Correspondence between scalp-EEG and stereoelectroencephalography seizure-onset patterns in patients with MRI-negative drug-resistant focal epilepsy[J]. Epilepsia Open, 2024, 9(2): 568-581.
26. Jahromi S, Matarrese M A G, Fabbri L, et al. Overlap of spike and ripple propagation onset predicts surgical outcome in epilepsy[J]. Ann Clin Transl Neurol, 2024, 11(10): 2530-2547.
27. Gulyaev S A. EEG microstate analysis and the EEG inverse problem solution as a tool for diagnosing cognitive dysfunctions in individuals who have had a mild form of COVID-19[J]. Hum Physiol, 2022, 48(5): 587-597.
28. Casta?o-Candamil S, H?hne J, Martínez-Vargas J D, et al. Solving the EEG inverse problem based on space-time-frequency structured sparsity constraints[J]. NeuroImage, 2015, 118: 598-612.
29. Frauscher B, Bartolomei F, Kobayashi K, et al. High-frequency oscillations: the state of clinical research[J]. Epilepsia, 2017, 58(8): 1316-1329.
30. Dimakopoulos V, Gotman J, Klimes P, et al. Multicentre analysis of seizure outcome predicted by removal of high-frequency oscillations[J]. Brain, 2025, 148(5): 1769-1777.
31. Ye H, Chen C, Weiss S A, et al. Pathological and physiological high-frequency oscillations on electroencephalography in patients with epilepsy[J]. Neurosci Bull, 2024, 40(5): 609-620.
32. Koessler L, Cecchin T, Colnat-Coulbois S, et al. Catching the invisible: mesial temporal source contribution to simultaneous EEG and SEEG recordings[J]. Brain Topogr, 2015, 28(1): 5-20.
33. Benoliel T, Arviv O, Doufish D, et al. Depth-to-scalp spatiotemporal dynamics for stereo-EEG[J]. Epilepsy Behav Rep, 2025, 31: 100784.
34. Cosandier-Rimélé D, Merlet I, Badier J M, et al. The neuronal sources of EEG: modeling of simultaneous scalp and intracerebral recordings in epilepsy[J]. NeuroImage, 2008, 42(1): 135-146.
35. von Ellenrieder N, Beltrachini L, Perucca P, et al. Size of cortical generators of epileptic interictal events and visibility on scalp EEG[J]. NeuroImage, 2014, 94: 47-54.
36. Tao J X, Baldwin M, Hawes-Ebersole S, et al. Cortical substrates of scalp EEG epileptiform discharges[J]. J Clin Neurophysiol, 2007, 24(2): 96-100.
37. Merlet I, Gotman J. Reliability of dipole models of epileptic spikes[J]. Clin Neurophysiol, 1999, 110(6): 1013-1028.
38. Takenaka M, Pflieger M E, Hori T, et al. Detectability in scalp EEGs of epileptic spikes emitted from brain electrical sources of different sizes and locations: a simulation study using realistic head models of elderly adults[J]. Clin EEG Neurosci, 2025, 56(4): 358-371.
39. Ramantani G, Dümpelmann M, Koessler L, et al. Simultaneous subdural and scalp EEG correlates of frontal lobe epileptic sources[J]. Epilepsia, 2014, 55(2): 278-288.
40. Casale M J, Marcuse L V, Young J J, et al. The sensitivity of scalp EEG at detecting seizures—a simultaneous scalp and stereo EEG study[J]. J Clin Neurophysiol, 2022, 39(1): 78-84.
41. Kramer M A, Ostrowski L M, Song D Y, et al. Scalp recorded spike ripples predict seizure risk in childhood epilepsy better than spikes[J]. Brain, 2019, 142(5): 1296-1309.
42. Abramovici S, Antony A, Baldwin M E, et al. Features of simultaneous scalp and intracranial EEG that predict localization of ictal onset zone[J]. Clin EEG Neurosci, 2018, 49(3): 206-212.

Journal of Biomedical Engineering

A study on the propagation characteristics of epileptic spike signals based on simultaneous intracranial and scalp electroencephalography

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