Advances in research on neuroelectrophysiological characteristics of post-stroke cognitive impairment based on quantitative electroencephalography and acupuncture interventions_Journal of Biomedical Engineering

Authors：

FENG Yachen ^1,2 , SU Kaiqi ¹ , REN Qiongdi ^1,2 , PAN Rui ^1,2 , WANG Chunxiao ^1,2 , ZHANG Xu ^1,2 , LI Qi ^1,2 , WANG Yaling ^1,2 ,  ZHANG Ming ¹

1. Department of Rehabilitation Center, the First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450000, P. R. China;
2. Rehabilitation Medicine College, Henan University of Chinese Medicine, Zhengzhou 450046, P. R. China;

Corresponding?author：

Keywords：

Stroke; Cognitive impairment; Quantitative electroencephalography; Acupuncture; Research progress

DOI：

10.7507/1001-5515.202602016

Video：

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Post-stroke cognitive impairment (PSCI) is a common complication of stroke that severely affects patients' quality of life and social functional recovery. Quantitative electroencephalography (QEEG), as a non-invasive neuroelectrophysiological technique with high temporal resolution, can reveal PSCI-related brain dysfunction and plasticity changes from multiple levels and dimensions, including neural oscillations, brain network connectivity, and dynamic optimization of brain function. However, its feature integration and efficacy evaluation system still require further refinement. In recent years, acupuncture has attracted increasing attention in the intervention of PSCI owing to its holistic regulatory effects and favorable safety profile. This review systematically integrates the characteristics of brain rhythms, brain functional networks, and dynamic brain activity in patients with PSCI, analyzes the associations between different electroencephalography (EEG) indicators and cognitive domains, and summarizes the multidimensional changes in EEG features following acupuncture intervention in PSCI. The aim is to provide evidence for a deeper understanding of the neuroelectrophysiological mechanisms underlying PSCI, while also offering references for the objective evaluation and modernization of acupuncture interventions.

Citation： FENG Yachen, SU Kaiqi, REN Qiongdi, PAN Rui, WANG Chunxiao, ZHANG Xu, LI Qi, WANG Yaling, ZHANG Ming. Advances in research on neuroelectrophysiological characteristics of post-stroke cognitive impairment based on quantitative electroencephalography and acupuncture interventions. Journal of Biomedical Engineering, 2026, 43(3): 661-668. doi: 10.7507/1001-5515.202602016 Copy

1.	Kelly M L, Lipior S, Schaefer S Y, et al. Standardizing the measurement and definition of post-stroke cognitive impairment: implications for stroke recovery and rehabilitation. Neurorehabil Neural Repair, 2026, 40(3): 246-257.
2.	He A, Wang Z, Wu X, et al. Incidence of post-stroke cognitive impairment in patients with first-ever ischemic stroke: a multicenter cross-sectional study in China. Lancet Reg Health West Pac, 2023, 33: 100687.
3.	Zhou W, Feng H, Tao H, et al. Factors influencing poststroke cognitive dysfunction: cross-sectional analysis. JMIR Form Res, 2024, 8: e59572.
4.	馬玉霞, 楊依依, 魏曉琴, 等. 卒中后認知障礙評估工具篩查準確性的Meta分析. 中國全科醫學, 2024, 27(32): 4066-4076.
5.	Zangeneh Soroush M, Zeng Y. EEG-based study of design creativity: a review on research design, experiments, and analysis. Front Behav Neurosci, 2024, 18: 1331396.
6.	Wijaya A, Setiawan N A, Ahmad A H, et al. Electroencephalography and mild cognitive impairment research: a scoping review and bibliometric analysis (ScoRBA). AIMS Neurosci, 2023, 10(2): 154-171.
7.	任瓊迪, 張銘. 腦卒中后認知障礙的中樞機制: 基于腦電圖和磁共振成像的研究進展. 中山大學學報(醫學科學版), 2025, 46(1): 61-69.
8.	Chaudhary U. Non-invasive brain signal acquisition techniques. Cham: Springer Nature Switzerland, 2025: 25-80.
9.	Petri S, Vitali H, Campus C, et al. Exploring neurodevelopment through oscillatory and aperiodic EEG activity: methodological and clinical consideration. Front Hum Neurosci, 2025, 19: 1641840.
10.	周書顏. 基于靜息腦電的卒中后認知障礙生物標志物的探索性研究. 廣州: 南方醫科大學, 2025.
11.	Spoa M, Monti S, Bjeki? J, et al. Resting-state EEG changes associated with cognitive decline in Parkinson's disease: a systematic review. J Neural Transm, 2026, 133(4): 731-765.
12.	Di Gregorio F, Lullini G, Orlandi S, et al. Clinical and neurophysiological predictors of the functional outcome in right-hemisphere stroke. Neuroimage, 2025, 308: 121059.
13.	Shpakivska-Bilan D, Susi G, Zhou D W, et al. High-power transient 12~30 Hz beta event features as early biomarkers of Alzheimer's disease conversion: an MEG study. Imaging Neurosci, 2025, 3: IMAG.a.69.
14.	Arioli M, Mattersberger M, Hoehl S, et al. Peak alpha frequency is linked to visual temporal attention in 6-month-olds. Sci Rep, 2024, 14(1): 28173.
15.	Zhao Y, Shi H, Kong W, et al. Peak alpha frequency as an objective biomarker for cognitive assessment in post-stroke cognitive impairment. Front Aging Neurosci, 2025, 17: 1639970.
16.	Hadiyoso S, Ong P A, Zakaria H, et al. EEG-based spectral dynamic in characterization of poststroke patients with cognitive impairment for early detection of vascular dementia. J Healthc Eng, 2022, 2022: 5666229.
17.	Ranasinghe P V N N, Mapa M S T. Functional connectivity and cognitive decline: a review of rs-fMRI, EEG, MEG, and graph theory approaches in aging and dementia. Explor Med, 2024, 5(6): 797-821.
18.	Kawano T, Hattori N, Uno Y, et al. Association between aphasia severity and brain network alterations after stroke assessed using the electroencephalographic phase synchrony index. Sci Rep, 2021, 11(1): 12469.
19.	Kawano T, Hattori N, Uno Y, et al. Electroencephalographic phase synchrony index as a biomarker of post-stroke aphasia recovery. Neurorehabil Neural Repair, 2025, 39(10): 839-850.
20.	Sarmukadam K, Behroozmand R. Neural oscillations reveal disrupted functional connectivity associated with impaired speech auditory feedback control in post-stroke aphasia. Cortex, 2023, 166: 258-274.
21.	Lee M, Hong Y, An S, et al. Machine learning-based prediction of post-stroke cognitive status using electroencephalography-derived brain network attributes. Front Aging Neurosci, 2023, 15: 1238274.
22.	Zhang H, Yang X, Yao L, et al. EEG microstates analysis after TMS in patients with subacute stroke during the resting state. Cereb Cortex, 2024, 34(1): bhad480.
23.	王海力, 尹寧, 徐桂芝. 腦電圖微狀態分析及應用研究進展. 生物醫學工程學雜志, 2023, 40(1): 163-170.
24.	Wang X, Song J, Kong W, et al. Identification and validation of an interpretable EEG-based machine learning model for the diagnosis of post-stroke cognitive impairment. Front Aging Neurosci, 2026, 17: 1700771.
25.	Kong W, Wang X, Song J, et al. Characteristics of EEG microstates in stroke patients with cognitive impairment after basal ganglia injury. Brain Res, 2025, 1863: 149716.
26.	丁思元, 朱燕, 施暢, 等. 基于靜息態與面孔情緒詞任務的失語癥患者抑郁狀態腦電特征研究. 生物醫學工程學雜志, 2025, 42(3): 488-495.
27.	Lu Z, Guo J, Sun J, et al. The event-related potential components across psychiatric disorders: a systematic review and network meta-analysis. Mol Psychiatry, 2025, 30(9): 4422-4431.
28.	Higashino T, Wakamiya N. Revisiting the model human processor: a neurophysiological investigation based on P300 and bereitschaftspotential. Front Hum Neurosci, 2025, 19: 1690746.
29.	Stahlhut L, Grotemeyer K H, Husstedt I W, et al. The impact of stroke on cognitive processing-a prospective event-related potential study. J Neurol Sci, 2014, 339(1-2): 157-163.
30.	馬喆喆, 鞏尊科, 溫煒婷, 等. 腦卒中注意障礙患者事件相關電位P300與注意評定量表的相關性分析. 中國康復醫學雜志, 2022, 37(8): 1113-1115.
31.	Xu M, Zhang Y, Zhang Y, et al. EEG biomarkers analysis in different cognitive impairment after stroke: an exploration study. Front Neurol, 2024, 15: 1358167.
32.	Yuan X, Ling Q, Yang N, et al. Cognitive potential characteristics and brain network dynamics in patients with acute cerebellar ischemic stroke: insights from P300 and moving dipoles. Cerebellum, 2025, 24(5): 121.
33.	鄭斯嘉, 尤紅, 張敏, 等. 針刺對缺血性腦卒中后認知及軀體運動功能障礙康復研究進展. 中華中醫藥學刊, 2025, 43(4): 225-229.
34.	Luo Z, Li W, Jiang J, et al. Effect of acupuncture on cognitive function in patients with post-stroke cognitive impairment: a systematic review and meta-analysis. Brain Behav, 2024, 14(10): e70075.
35.	Yang S, Bao Q, Zhong W, et al. Acupuncture on post stroke cognitive impairment: a systematic review of neuroimaging studies. J Multidiscip Healthc, 2025, 18: 6391-6410.
36.	隋雪. 應用EEG功率譜分析電針對腦梗死相關失眠患者睡眠及認知功能的影響. 哈爾濱: 黑龍江中醫藥大學, 2025.
37.	Wei C, Chen J, Yang Q, et al. Effects of manual acupuncture versus sham acupuncture in patients with post stroke depression: a randomized clinical trial. Neurol Ther, 2024, 13(6): 1717-1735.
38.	韋冰心, 劉國成, 曾鑒源. 頭針運動針刺法聯合認知功能訓練治療腦卒中后認知障礙的臨床觀察. 廣州中醫藥大學學報, 2023, 40(2): 368-374.
39.	李慎微, 王東巖, 劉月, 等. 不同針刺方式刺激認知情感區對卒中后認知障礙患者腦電圖微狀態的影響. 中國針灸, 2026, 46. DOI: 10.13703/j.0255-2930.20250616-0007.
40.	Wu R, Ma H, Hu J, et al. Electroacupuncture stimulation to modulate neural oscillations in promoting neurological rehabilitation. Brain Res, 2024, 1822: 148642.
41.	Zhou H, Han Y, Xie D, et al. Predictors and clinical implications of post-stroke cognitive impairment: a retrospective study. Sci Rep, 2025, 15(1): 24198.
42.	Soleimani B, Dallasta I, Das P, et al. Altered directional functional connectivity underlies post stroke cognitive recovery. Brain Commun, 2023, 5(3): fcad149.
43.	Xu M, Zhang B, Chen Y, et al. An innovation scalp acupuncture prescription for post-stroke aphasia: a neuroimaging-based validation study. Brain Res Bull, 2025, 225: 111334.
44.	Chang X, Hao P, Zhang S, et al. Multi-scale analysis of acupuncture mechanisms for motor and sensory cortex activity based on SEEG data. Cereb Cortex, 2024, 34(4): bhae127.
45.	Zhang Y, Ma Y, Gao Y L, et al. Abnormalities of resting-state EEG microstates in older adults with cognitive frailty. Geroscience, 2025, 47(3): 3417-3431.
46.	Li N, Wang H, Liu H, et al. The effects and mechanisms of acupuncture for post-stroke cognitive impairment: progress and prospects. Front Neurosci, 2023, 17: 1211044.

1. Kelly M L, Lipior S, Schaefer S Y, et al. Standardizing the measurement and definition of post-stroke cognitive impairment: implications for stroke recovery and rehabilitation. Neurorehabil Neural Repair, 2026, 40(3): 246-257.
2. He A, Wang Z, Wu X, et al. Incidence of post-stroke cognitive impairment in patients with first-ever ischemic stroke: a multicenter cross-sectional study in China. Lancet Reg Health West Pac, 2023, 33: 100687.
3. Zhou W, Feng H, Tao H, et al. Factors influencing poststroke cognitive dysfunction: cross-sectional analysis. JMIR Form Res, 2024, 8: e59572.
4. 馬玉霞, 楊依依, 魏曉琴, 等. 卒中后認知障礙評估工具篩查準確性的Meta分析. 中國全科醫學, 2024, 27(32): 4066-4076.
5. Zangeneh Soroush M, Zeng Y. EEG-based study of design creativity: a review on research design, experiments, and analysis. Front Behav Neurosci, 2024, 18: 1331396.
6. Wijaya A, Setiawan N A, Ahmad A H, et al. Electroencephalography and mild cognitive impairment research: a scoping review and bibliometric analysis (ScoRBA). AIMS Neurosci, 2023, 10(2): 154-171.
7. 任瓊迪, 張銘. 腦卒中后認知障礙的中樞機制: 基于腦電圖和磁共振成像的研究進展. 中山大學學報(醫學科學版), 2025, 46(1): 61-69.
8. Chaudhary U. Non-invasive brain signal acquisition techniques. Cham: Springer Nature Switzerland, 2025: 25-80.
9. Petri S, Vitali H, Campus C, et al. Exploring neurodevelopment through oscillatory and aperiodic EEG activity: methodological and clinical consideration. Front Hum Neurosci, 2025, 19: 1641840.
10. 周書顏. 基于靜息腦電的卒中后認知障礙生物標志物的探索性研究. 廣州: 南方醫科大學, 2025.
11. Spoa M, Monti S, Bjeki? J, et al. Resting-state EEG changes associated with cognitive decline in Parkinson's disease: a systematic review. J Neural Transm, 2026, 133(4): 731-765.
12. Di Gregorio F, Lullini G, Orlandi S, et al. Clinical and neurophysiological predictors of the functional outcome in right-hemisphere stroke. Neuroimage, 2025, 308: 121059.
13. Shpakivska-Bilan D, Susi G, Zhou D W, et al. High-power transient 12~30 Hz beta event features as early biomarkers of Alzheimer's disease conversion: an MEG study. Imaging Neurosci, 2025, 3: IMAG.a.69.
14. Arioli M, Mattersberger M, Hoehl S, et al. Peak alpha frequency is linked to visual temporal attention in 6-month-olds. Sci Rep, 2024, 14(1): 28173.
15. Zhao Y, Shi H, Kong W, et al. Peak alpha frequency as an objective biomarker for cognitive assessment in post-stroke cognitive impairment. Front Aging Neurosci, 2025, 17: 1639970.
16. Hadiyoso S, Ong P A, Zakaria H, et al. EEG-based spectral dynamic in characterization of poststroke patients with cognitive impairment for early detection of vascular dementia. J Healthc Eng, 2022, 2022: 5666229.
17. Ranasinghe P V N N, Mapa M S T. Functional connectivity and cognitive decline: a review of rs-fMRI, EEG, MEG, and graph theory approaches in aging and dementia. Explor Med, 2024, 5(6): 797-821.
18. Kawano T, Hattori N, Uno Y, et al. Association between aphasia severity and brain network alterations after stroke assessed using the electroencephalographic phase synchrony index. Sci Rep, 2021, 11(1): 12469.
19. Kawano T, Hattori N, Uno Y, et al. Electroencephalographic phase synchrony index as a biomarker of post-stroke aphasia recovery. Neurorehabil Neural Repair, 2025, 39(10): 839-850.
20. Sarmukadam K, Behroozmand R. Neural oscillations reveal disrupted functional connectivity associated with impaired speech auditory feedback control in post-stroke aphasia. Cortex, 2023, 166: 258-274.
21. Lee M, Hong Y, An S, et al. Machine learning-based prediction of post-stroke cognitive status using electroencephalography-derived brain network attributes. Front Aging Neurosci, 2023, 15: 1238274.
22. Zhang H, Yang X, Yao L, et al. EEG microstates analysis after TMS in patients with subacute stroke during the resting state. Cereb Cortex, 2024, 34(1): bhad480.
23. 王海力, 尹寧, 徐桂芝. 腦電圖微狀態分析及應用研究進展. 生物醫學工程學雜志, 2023, 40(1): 163-170.
24. Wang X, Song J, Kong W, et al. Identification and validation of an interpretable EEG-based machine learning model for the diagnosis of post-stroke cognitive impairment. Front Aging Neurosci, 2026, 17: 1700771.
25. Kong W, Wang X, Song J, et al. Characteristics of EEG microstates in stroke patients with cognitive impairment after basal ganglia injury. Brain Res, 2025, 1863: 149716.
26. 丁思元, 朱燕, 施暢, 等. 基于靜息態與面孔情緒詞任務的失語癥患者抑郁狀態腦電特征研究. 生物醫學工程學雜志, 2025, 42(3): 488-495.
27. Lu Z, Guo J, Sun J, et al. The event-related potential components across psychiatric disorders: a systematic review and network meta-analysis. Mol Psychiatry, 2025, 30(9): 4422-4431.
28. Higashino T, Wakamiya N. Revisiting the model human processor: a neurophysiological investigation based on P300 and bereitschaftspotential. Front Hum Neurosci, 2025, 19: 1690746.
29. Stahlhut L, Grotemeyer K H, Husstedt I W, et al. The impact of stroke on cognitive processing-a prospective event-related potential study. J Neurol Sci, 2014, 339(1-2): 157-163.
30. 馬喆喆, 鞏尊科, 溫煒婷, 等. 腦卒中注意障礙患者事件相關電位P300與注意評定量表的相關性分析. 中國康復醫學雜志, 2022, 37(8): 1113-1115.
31. Xu M, Zhang Y, Zhang Y, et al. EEG biomarkers analysis in different cognitive impairment after stroke: an exploration study. Front Neurol, 2024, 15: 1358167.
32. Yuan X, Ling Q, Yang N, et al. Cognitive potential characteristics and brain network dynamics in patients with acute cerebellar ischemic stroke: insights from P300 and moving dipoles. Cerebellum, 2025, 24(5): 121.
33. 鄭斯嘉, 尤紅, 張敏, 等. 針刺對缺血性腦卒中后認知及軀體運動功能障礙康復研究進展. 中華中醫藥學刊, 2025, 43(4): 225-229.
34. Luo Z, Li W, Jiang J, et al. Effect of acupuncture on cognitive function in patients with post-stroke cognitive impairment: a systematic review and meta-analysis. Brain Behav, 2024, 14(10): e70075.
35. Yang S, Bao Q, Zhong W, et al. Acupuncture on post stroke cognitive impairment: a systematic review of neuroimaging studies. J Multidiscip Healthc, 2025, 18: 6391-6410.
36. 隋雪. 應用EEG功率譜分析電針對腦梗死相關失眠患者睡眠及認知功能的影響. 哈爾濱: 黑龍江中醫藥大學, 2025.
37. Wei C, Chen J, Yang Q, et al. Effects of manual acupuncture versus sham acupuncture in patients with post stroke depression: a randomized clinical trial. Neurol Ther, 2024, 13(6): 1717-1735.
38. 韋冰心, 劉國成, 曾鑒源. 頭針運動針刺法聯合認知功能訓練治療腦卒中后認知障礙的臨床觀察. 廣州中醫藥大學學報, 2023, 40(2): 368-374.
39. 李慎微, 王東巖, 劉月, 等. 不同針刺方式刺激認知情感區對卒中后認知障礙患者腦電圖微狀態的影響. 中國針灸, 2026, 46. DOI: 10.13703/j.0255-2930.20250616-0007.
40. Wu R, Ma H, Hu J, et al. Electroacupuncture stimulation to modulate neural oscillations in promoting neurological rehabilitation. Brain Res, 2024, 1822: 148642.
41. Zhou H, Han Y, Xie D, et al. Predictors and clinical implications of post-stroke cognitive impairment: a retrospective study. Sci Rep, 2025, 15(1): 24198.
42. Soleimani B, Dallasta I, Das P, et al. Altered directional functional connectivity underlies post stroke cognitive recovery. Brain Commun, 2023, 5(3): fcad149.
43. Xu M, Zhang B, Chen Y, et al. An innovation scalp acupuncture prescription for post-stroke aphasia: a neuroimaging-based validation study. Brain Res Bull, 2025, 225: 111334.
44. Chang X, Hao P, Zhang S, et al. Multi-scale analysis of acupuncture mechanisms for motor and sensory cortex activity based on SEEG data. Cereb Cortex, 2024, 34(4): bhae127.
45. Zhang Y, Ma Y, Gao Y L, et al. Abnormalities of resting-state EEG microstates in older adults with cognitive frailty. Geroscience, 2025, 47(3): 3417-3431.
46. Li N, Wang H, Liu H, et al. The effects and mechanisms of acupuncture for post-stroke cognitive impairment: progress and prospects. Front Neurosci, 2023, 17: 1211044.

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