Application of functional near-infrared spectroscopy in stroke-related neurological function research_West China Medical Journal

Authors：

ZHAN Xiaoxuan ¹ , HUANG Yuping ² , PAN Jingjing ¹ , SUI Yanfang ¹ , ZENG Huizi ¹ , WU Jing ¹ ,  SONG Zhenhua ¹

1. Department of Rehabilitation Medicine, Haikou Affiliated Hospital of Central South University Xiangya School of Medicine, Haikou, Hainan 570203, P. R. China;
2. School of Rehabilitation Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250355, P. R. China;

Corresponding author：

SONG Zhenhua, Email: szh@163.com

Keywords：

Functional near-infrared spectroscopy; stroke; neurological function; rehabilitation

DOI：

10.7507/1002-0179.202503253

Video：

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Functional near-infrared spectroscopy (fNIRS), as an emerging brain imaging technique, has gradually become an important tool for stroke-related neurological function research due to its advantages of non-invasiveness, exercise tolerance, and portability. This article summarizes the application of fNIRS in evaluating neurological dysfunction, identifying functional injury sites, and monitoring rehabilitation outcomes, analyzes the advantages and disadvantages demonstrated in research and explores future improvement directions to promote further development of fNIRS in clinical applications.

Citation： ZHAN Xiaoxuan, HUANG Yuping, PAN Jingjing, SUI Yanfang, ZENG Huizi, WU Jing, SONG Zhenhua. Application of functional near-infrared spectroscopy in stroke-related neurological function research. West China Medical Journal, 2025, 40(6): 979-983. doi: 10.7507/1002-0179.202503253 Copy

1.	GBD 2021 Diseases and Injuries Collaborators. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet, 2024, 403(10440): 2133-2161.
2.	夏达建, 谢云芳, 张冬梅, 等. 1982-2021 年中国缺血性脑卒中死亡趋势及年龄-时期-队列效应分析. 现代预防医学, 2025, 52(4): 590-596, 607.
3.	Schumacher R, Halai AD, Lambon Ralph MA. Assessing and mapping language, attention and executive multidimensional deficits in stroke aphasia. Brain, 2019, 142(10): 3202-3216.
4.	Kuipers JA, Hoffman N, Carrick FR, et al. Post-stroke rehabilitation: neurophysiology processes of bilateral movement training and interlimb coupling-a systematic review. J Clin Med, 2025, 14(11): 3757.
5.	Wang J, Zhou J, Zhu J, et al. Brain remodeling in stroke patients: a comprehensive review of mechanistic and neuroimaging studies. Behav Brain Res, 2025, 486: 115548.
6.	Liu M, Wan C, Wang C, et al. Predicting upper limb motor dysfunction after ischemic stroke: a functional near-infrared spectroscopy-based nomogram model. Front Neurol, 2025, 16: 1524851.
7.	Zhao YN, Han PP, Zhang XY, et al. Applications of functional near-infrared spectroscopy (fNIRS) neuroimaging during rehabilitation following stroke: a review. Med Sci Monit, 2024, 30: e943785.
8.	Bonilauri A, Pirastru A, Sangiuliano Intra F, et al. Surface-based integration approach for fNIRS-fMRI reliability assessment. J Neurosci Methods, 2023, 398: 109952.
9.	Lee G, Lee J, Kim J, et al. Whole brain hemodynamic response based on synchrony analysis of brain signals for effective application of HD-tDCS in stroke patients: an fNIRS study. J Pers Med, 2022, 12(3): 432.
10.	Li R, Li S, Roh J, et al. Multimodal neuroimaging using concurrent EEG/fNIRS for poststroke recovery assessment: an exploratory study. Neurorehabil Neural Repair, 2020, 34(12): 1099-1110.
11.	Cai G, Xu J, Zhang C, et al. Identifying biomarkers related to motor function in chronic stroke: a fNIRS and TMS study. CNS Neurosci Ther, 2024, 30(7): e14889.
12.	Arun KM, Smitha KA, Sylaja PN, et al. Identifying resting-state functional connectivity changes in the motor cortex using fNIRS during recovery from stroke. Brain Topogr, 2020, 33(6): 710-719.
13.	Sui Y, Kan C, Zhu S, et al. Resting-state functional connectivity for determining outcomes in upper extremity function after stroke: a functional near-infrared spectroscopy study. Front Neurol, 2022, 13: 965856.
14.	Pang R, Wang D, Chen TSR, et al. Reorganization of prefrontal network in stroke patients with dyskinesias: evidence from resting-state functional near-infrared spectroscopy. J Biophotonics, 2022, 15(7): e202200014.
15.	Huo C, Xu G, Li Z, et al. Limb linkage rehabilitation training-related changes in cortical activation and effective connectivity after stroke: a functional near-infrared spectroscopy study. Sci Rep, 2019, 9(1): 6226.
16.	Allegra M, Favaretto C, Metcalf N, et al. Stroke-related alterations in inter-areal communication. Neuroimage Clin, 2021, 32: 102812.
17.	Cirillo C, Brihmat N, Castel-Lacanal E, et al. Post-stroke remodeling processes in animal models and humans. J Cereb Blood Flow Metab, 2020, 40(1): 3-22.
18.	金涛, 李浩正, 鲍春蓉, 等. 脑卒中后认知功能障碍患者的功能性近红外脑网络特征分析. 康复学报, 2024, 34(4): 341-348.
19.	Kong Y, Peng W, Li J, et al. Alteration in brain functional connectivity in patients with post-stroke cognitive impairment during memory task: a fNIRS study. J Stroke Cerebrovasc Dis, 2023, 32(9): 107280.
20.	Duan C, Chong Y, Gong J, et al. An fNIRS-based investigation of cerebral hemodynamic responses during verbal fluency task and n-back task in individuals with mild cognitive impairment. Front Neurol, 2025, 16: 1571964.
21.	Bai Z, Fong KNK. “Remind-to-Move” treatment enhanced activation of the primary motor cortex in patients with stroke. Brain Topogr, 2020, 33(2): 275-283.
22.	Sun X, Dai C, Wu X, et al. Current implications of EEG and fNIRS as functional neuroimaging techniques for motor recovery after stroke. Med Rev (2021), 2024, 4(6): 492-509.
23.	Song Y, Sun Z, Sun W, et al. Neuroplasticity following stroke from a functional laterality perspective: a fNIRS study. Brain Topogr, 2023, 36(3): 283-293.
24.	Obayashi S. Cognitive and linguistic dysfunction after thalamic stroke and recovery process: possible mechanism. AIMS Neurosci, 2021, 9(1): 1-11.
25.	Obayashi S. The supplementary motor area responsible for word retrieval decline after acute thalamic stroke revealed by coupled SPECT and near-infrared spectroscopy. Brain Sci, 2020, 10(4): 247.
26.	Lee Friesen C, Lawrence M, Ingram TGJ, et al. Home-based portable fNIRS-derived cortical laterality correlates with impairment and function in chronic stroke. Front Hum Neurosci, 2022, 16: 1023246.
27.	Zou J, Yin Y, Lin Z, et al. The analysis of brain functional connectivity of post-stroke cognitive impairment patients: an fNIRS study. Front Neurosci, 2023, 17: 1168773.
28.	Sun J, Wang D, Chen S, et al. The behavioral significance of resting state network after stroke: a study via graph theory analysis with near-infrared spectroscopy. Med Nov Technol Devices, 2021, 11: 100083.
29.	Huo C, Sun Z, Xu G, et al. fNIRS-based brain functional response to robot-assisted training for upper-limb in stroke patients with hemiplegia. Front Aging Neurosci, 2022, 14: 1060734.
30.	Yang Z, Ye L, Yang L, et al. Early screening of post-stroke fall risk: a simultaneous multimodal fNIRs-EMG study. CNS Neurosci Ther, 2024, 30(9): e70041.
31.	李鑫鑫, 卜令国. 基于 fNIRS 和神经反馈的记忆认知训练研究. 中国医疗器械杂志, 2024, 48(2): 132-137.
32.	Matarasso AK, Rieke JD, White K, et al. Combined real-time fMRI and real time fNIRS brain computer interface (BCI): training of volitional wrist extension after stroke, a case series pilot study. PLoS One, 2021, 16(5): e0250431.
33.	Kohl SH, Mehler DMA, Lührs M, et al. The Potential of functional near-infrared spectroscopy-based neurofeedback-a systematic review and recommendations for best practice. Front Neurosci, 2020, 14: 594.
34.	Ni J, Jiang W, Gong X, et al. Effect of rTMS intervention on upper limb motor function after stroke: a study based on fNIRS. Front Aging Neurosci, 2023, 14: 1077218.
35.	Zinos A, Wagner JC, Beardsley SA, et al. Spatial correspondence of cortical activity measured with whole head fNIRS and fMRI: toward clinical use within subject. Neuroimage, 2024, 290: 120569.
36.	Khan AM, Akram MU, Nazir S, et al. Multi-head deep learning framework for pulmonary disease detection and severity scoring with modified progressive learning. Biomed Signal Process Control, 2023, 85: 104855.

1. GBD 2021 Diseases and Injuries Collaborators. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet, 2024, 403(10440): 2133-2161.
2. 夏达建, 谢云芳, 张冬梅, 等. 1982-2021 年中国缺血性脑卒中死亡趋势及年龄-时期-队列效应分析. 现代预防医学, 2025, 52(4): 590-596, 607.
3. Schumacher R, Halai AD, Lambon Ralph MA. Assessing and mapping language, attention and executive multidimensional deficits in stroke aphasia. Brain, 2019, 142(10): 3202-3216.
4. Kuipers JA, Hoffman N, Carrick FR, et al. Post-stroke rehabilitation: neurophysiology processes of bilateral movement training and interlimb coupling-a systematic review. J Clin Med, 2025, 14(11): 3757.
5. Wang J, Zhou J, Zhu J, et al. Brain remodeling in stroke patients: a comprehensive review of mechanistic and neuroimaging studies. Behav Brain Res, 2025, 486: 115548.
6. Liu M, Wan C, Wang C, et al. Predicting upper limb motor dysfunction after ischemic stroke: a functional near-infrared spectroscopy-based nomogram model. Front Neurol, 2025, 16: 1524851.
7. Zhao YN, Han PP, Zhang XY, et al. Applications of functional near-infrared spectroscopy (fNIRS) neuroimaging during rehabilitation following stroke: a review. Med Sci Monit, 2024, 30: e943785.
8. Bonilauri A, Pirastru A, Sangiuliano Intra F, et al. Surface-based integration approach for fNIRS-fMRI reliability assessment. J Neurosci Methods, 2023, 398: 109952.
9. Lee G, Lee J, Kim J, et al. Whole brain hemodynamic response based on synchrony analysis of brain signals for effective application of HD-tDCS in stroke patients: an fNIRS study. J Pers Med, 2022, 12(3): 432.
10. Li R, Li S, Roh J, et al. Multimodal neuroimaging using concurrent EEG/fNIRS for poststroke recovery assessment: an exploratory study. Neurorehabil Neural Repair, 2020, 34(12): 1099-1110.
11. Cai G, Xu J, Zhang C, et al. Identifying biomarkers related to motor function in chronic stroke: a fNIRS and TMS study. CNS Neurosci Ther, 2024, 30(7): e14889.
12. Arun KM, Smitha KA, Sylaja PN, et al. Identifying resting-state functional connectivity changes in the motor cortex using fNIRS during recovery from stroke. Brain Topogr, 2020, 33(6): 710-719.
13. Sui Y, Kan C, Zhu S, et al. Resting-state functional connectivity for determining outcomes in upper extremity function after stroke: a functional near-infrared spectroscopy study. Front Neurol, 2022, 13: 965856.
14. Pang R, Wang D, Chen TSR, et al. Reorganization of prefrontal network in stroke patients with dyskinesias: evidence from resting-state functional near-infrared spectroscopy. J Biophotonics, 2022, 15(7): e202200014.
15. Huo C, Xu G, Li Z, et al. Limb linkage rehabilitation training-related changes in cortical activation and effective connectivity after stroke: a functional near-infrared spectroscopy study. Sci Rep, 2019, 9(1): 6226.
16. Allegra M, Favaretto C, Metcalf N, et al. Stroke-related alterations in inter-areal communication. Neuroimage Clin, 2021, 32: 102812.
17. Cirillo C, Brihmat N, Castel-Lacanal E, et al. Post-stroke remodeling processes in animal models and humans. J Cereb Blood Flow Metab, 2020, 40(1): 3-22.
18. 金涛, 李浩正, 鲍春蓉, 等. 脑卒中后认知功能障碍患者的功能性近红外脑网络特征分析. 康复学报, 2024, 34(4): 341-348.
19. Kong Y, Peng W, Li J, et al. Alteration in brain functional connectivity in patients with post-stroke cognitive impairment during memory task: a fNIRS study. J Stroke Cerebrovasc Dis, 2023, 32(9): 107280.
20. Duan C, Chong Y, Gong J, et al. An fNIRS-based investigation of cerebral hemodynamic responses during verbal fluency task and n-back task in individuals with mild cognitive impairment. Front Neurol, 2025, 16: 1571964.
21. Bai Z, Fong KNK. “Remind-to-Move” treatment enhanced activation of the primary motor cortex in patients with stroke. Brain Topogr, 2020, 33(2): 275-283.
22. Sun X, Dai C, Wu X, et al. Current implications of EEG and fNIRS as functional neuroimaging techniques for motor recovery after stroke. Med Rev (2021), 2024, 4(6): 492-509.
23. Song Y, Sun Z, Sun W, et al. Neuroplasticity following stroke from a functional laterality perspective: a fNIRS study. Brain Topogr, 2023, 36(3): 283-293.
24. Obayashi S. Cognitive and linguistic dysfunction after thalamic stroke and recovery process: possible mechanism. AIMS Neurosci, 2021, 9(1): 1-11.
25. Obayashi S. The supplementary motor area responsible for word retrieval decline after acute thalamic stroke revealed by coupled SPECT and near-infrared spectroscopy. Brain Sci, 2020, 10(4): 247.
26. Lee Friesen C, Lawrence M, Ingram TGJ, et al. Home-based portable fNIRS-derived cortical laterality correlates with impairment and function in chronic stroke. Front Hum Neurosci, 2022, 16: 1023246.
27. Zou J, Yin Y, Lin Z, et al. The analysis of brain functional connectivity of post-stroke cognitive impairment patients: an fNIRS study. Front Neurosci, 2023, 17: 1168773.
28. Sun J, Wang D, Chen S, et al. The behavioral significance of resting state network after stroke: a study via graph theory analysis with near-infrared spectroscopy. Med Nov Technol Devices, 2021, 11: 100083.
29. Huo C, Sun Z, Xu G, et al. fNIRS-based brain functional response to robot-assisted training for upper-limb in stroke patients with hemiplegia. Front Aging Neurosci, 2022, 14: 1060734.
30. Yang Z, Ye L, Yang L, et al. Early screening of post-stroke fall risk: a simultaneous multimodal fNIRs-EMG study. CNS Neurosci Ther, 2024, 30(9): e70041.
31. 李鑫鑫, 卜令国. 基于 fNIRS 和神经反馈的记忆认知训练研究. 中国医疗器械杂志, 2024, 48(2): 132-137.
32. Matarasso AK, Rieke JD, White K, et al. Combined real-time fMRI and real time fNIRS brain computer interface (BCI): training of volitional wrist extension after stroke, a case series pilot study. PLoS One, 2021, 16(5): e0250431.
33. Kohl SH, Mehler DMA, Lührs M, et al. The Potential of functional near-infrared spectroscopy-based neurofeedback-a systematic review and recommendations for best practice. Front Neurosci, 2020, 14: 594.
34. Ni J, Jiang W, Gong X, et al. Effect of rTMS intervention on upper limb motor function after stroke: a study based on fNIRS. Front Aging Neurosci, 2023, 14: 1077218.
35. Zinos A, Wagner JC, Beardsley SA, et al. Spatial correspondence of cortical activity measured with whole head fNIRS and fMRI: toward clinical use within subject. Neuroimage, 2024, 290: 120569.
36. Khan AM, Akram MU, Nazir S, et al. Multi-head deep learning framework for pulmonary disease detection and severity scoring with modified progressive learning. Biomed Signal Process Control, 2023, 85: 104855.

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