基于脑-机接口的针刺手法量学规范化研究

金传阳; 朱海滨; 熊嘉玮; 张建斌

doi:10.14148/j.issn.1672-0482.2021.0587

基于脑-机接口的针刺手法量学规范化研究

doi: 10.14148/j.issn.1672-0482.2021.0587

南京中医药大学第二附属医院，江苏南京 210017

基金项目:

国家自然科学基金 81973947

南京中医药大学自然科学基金 XZR2020053

详细信息

作者简介:
金传阳，男，博士研究生，E-mail：laopenti2011@163.com

通讯作者:
张建斌，男，教授, 主要从事针灸理论与临床转化的研究，E-mail：zhangjianbin@njucm.edu.cn

中图分类号: R245.3
计量
- 文章访问数: 278
- HTML全文浏览量: 66
- PDF下载量: 137
- 被引次数: 0
出版历程
- 收稿日期: 2021-04-25
- 网络出版日期: 2021-12-21
- 刊出日期: 2021-07-10
- 发布日期: 2021-07-15

Standardization Research on Quantification of Acupuncture Manipulation Stimuli Based on Brain-Computer Interface

The Second Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210017, China

摘要

摘要: 基于脑-机接口技术分析针刺治疗中相关刺激量和效应评价等相关问题，对针刺手法量学规范化研究作初步论述。提出基于脑-机接口的针刺手法量学研究特点包括数据量巨大、数据流稳健、客观量化和自由度分析高等。认为针灸临床视角下的脑-机接口数据获取重点包括了神经元网络整体联结性，特定脑区活动，针刺干预中机体耐受/痛阈波动，皮质不同板层神经元动力学改变等4方面。以针灸干预中风后康复的疗效评价为例，说明基于脑-机接口的针刺手法量学规范化的研究特点和潜在优势。
- 针刺 /
- 刺激量 /
- 规范化 /
- 脑-机接口 /
- 神经电生理
Abstract: Based on the brain-computer interface technology, we analyzed the problems related to the number of stimuli and treatment effect of acupuncture, so as to make a preliminary overview about standardization research on the quantification of acupuncture manipulation stimuli. It is proposed that the characteristics of the quantitative study of acupuncture manipulation stimuli based on a brain-computer interface include a large amount of data, stable data flow, as well as quantification and objection along with a high degree of freedom in analysis. It is suggested that the focus of data acquisition at the brain-computer interface from a clinical perspective of acupuncture manipulation includes four aspects: the overall connectivity of neural networks, the activity of specific brain areas, the fluctuation of body tolerance or pain threshold during acupuncture intervention, and the activity change of different lamina neurons of the cortex. The efficacy evaluation of acupuncture interventions in post-stroke rehabilitation is used as an example to illustrate the study characteristics and potential advantages of standardization research on the quantification of acupuncture manipulation stimuli based on brain-computer interface.
- acupuncture /
- quantity of stimuli /
- normalization /
- brain-machine interface /
- electrophysiology

HTML全文

参考文献(31)

[1]	KRUCOFF MO, RAHIMPOUR S, SLUTZKY MW, et al. Enhancing nervous system recovery through neurobiologics, neural interface training, and neurorehabilitation[J ]. Front Neurosci, 2016, 10: 584. http://www.researchgate.net/profile/Max_Krucoff/publication/311919389_Enhancing_Nervous_System_Recovery_through_Neurobiologics_Neural_Interface_Training_and_Neurorehabilitation/links/587d620c08ae9a860ff0fcec.pdf
[2]	VIDAL JJ. Toward direct brain-computer communication[J]. Annu Rev Biophys Bioeng, 1973, 2 : 157-180. doi: 10.1146/annurev.bb.02.060173.001105
[3]	LEVINE SP, HUGGINS JE, BEMENT SL, et al. A direct brain interface based on event-related potentials[J ]. IEEE Trans Rehabil Eng, 2000, 8(2) : 180-185. doi: 10.1109/86.847809
[4]	VANNESTE S, SONG JJ, DE RIDDER D. Thalamocortical dysrhythmia detected by machine learning[J]. Nat Commun, 2018, 9(1) : 1103. doi: 10.1038/s41467-018-02820-0
[5]	傅立新. 从针刺手法量学的系列研究看针灸科研与临床实践的关系[C]. 杭州: 中国针灸学会2009学术年会, 2009 : 2.
[6]	石学敏. 捻转补泻手法的应用及其量学概念[J]. 中国医药学报, 1987, 2(5) : 272-273. https://www.cnki.com.cn/Article/CJFDTOTAL-BXYY198705004.htm
[7]	朱琏. 新针灸学[M]. 南宁: 广西人民出版社, 1980: 11-16.
[8]	承淡安. 中国针灸学[M]. 北京: 人民卫生出版社, 1955 : 16.
[9]	王季春. 从针刺手法量学的系列研究看针灸科研与临床实践的关系[J]. 实用中医内科杂志, 2020: 1-4. https://www.cnki.com.cn/Article/CJFDTOTAL-SYZY202108046.htm
[10]	马旭, 沈婧蕾, 杨华元. 针刺手法参数采集及量效关系分析[J]. 上海针灸杂志, 2020, 39(11) : 1479-1482. https://www.cnki.com.cn/Article/CJFDTOTAL-SHZJ202011026.htm
[11]	CAI RL, SHEN GM, WANG H, et al. Brain functional connectivity network studies of acupuncture: A systematic review on resting-state fMRI[J]. JIntegr Med, 2018, 16(1) : 26-33. http://www.cqvip.com/QK/87110A/20181/674409085.html
[12]	张青, 余玲玲, 刘诗琴, 等. 关于针刺得气中枢响应的fMRI研究现状与思索[J]. 针刺研究, 2018, 43(5) : 330-334. https://www.cnki.com.cn/Article/CJFDTOTAL-XCYJ201805016.htm
[13]	李香淑, 胡佳慧, 鲁海, 等. 基于fMRI技术探讨电针与手针中枢机制响应差异[J]. 分子影像学杂志, 2020, 43 (1) : 12-15. https://www.cnki.com.cn/Article/CJFDTOTAL-FZYX202001030.htm
[14]	YADAV D, YADAV S, VEER K. A comprehensive assessment of brain computer interfaces: Recent trends and challenges[J]. J Neurosci Methods, 2020, 346 : 108918. doi: 10.1016/j.jneumeth.2020.108918
[15]	HUANG K, LIANG S, SUN Z, et al. Startup mechanism of moxibustion warming and dredging function[J]. Chin Acupunct Moxib, 2017, 37(9) : 1023-1026. http://europepmc.org/abstract/MED/29354927
[16]	CARLSON D, CARIN L. Continuing progress of spike sorting in the era of big data[J]. Curr Opin Neurobiol, 2019, 55 : 90- 96. doi: 10.1016/j.conb.2019.02.007
[17]	ZONG W, WU R, CHEN S, et al. Miniature two-photon microscopy for enlarged field-of-view, multi-plane and long-term brain imaging[J]. Nat Methods, 2021, 18(1) : 46-49. doi: 10.1038/s41592-020-01024-z
[18]	VON BARTHELD CS, BAHNEY J, HERCULANO - HOUZEL S. The search for true numbers of neurons and glial cells in the human brain: A review of 150 years of cell counting[J]. J Comp Neurol, 2016, 524(18) : 3865-3895. doi: 10.1002/cne.24040
[19]	OXLEY TJ, YOO PE, RIND GS, etal. Motor neuroprosthesis implanted with neurointerventional surgery improves capacity for activities of daily living tasks in severe paralysis: first in-human experience[J]. J Neurointerv Surg, 2021, 13 (2) : 102-108. doi: 10.1136/neurintsurg-2020-016862
[20]	SAHA S, MAMUN KA, AHMED K, etal. Progress in brain computer interface: Challenges and opportunities[J ]. Front Syst Neurosci, 2021, 15 : 578-875.
[21]	HE Z, LI Z, YANG F, etal. Advances in multimodal emotion recognition based on brain-computer interfaces[J]. Brain Sci, 2020, 10(10) : 687. doi: 10.3390/brainsci10100687
[22]	SU F, XU W. Enhancing brain plasticity to promote stroke recovery[J]. Front Neurol, 2020, 11 : 554089. doi: 10.3389/fneur.2020.554089
[23]	SMALL SL, BUCCINO G, SOLODKIN A. Brain repair after stroke: A novel neurological model[J ]. Nat Rev Neurol, 2013, 9(12) : 698-707. http://europepmc.org/abstract/med/24217509
[24]	DIMYAN MA, COHEN LG. Neuroplasticity in the context of motor rehabilitation after stroke[J]. Nat Rev Neurol, 2011, 7 (2) : 76-85. doi: 10.1038/nrneurol.2010.200
[25]	ZHANG R, LAO L, REN K, et al. Mechanisms of acupuncture-electroacupuncture on persistent pain[J ]. Anesthesiology, 2014, 120(2) : 482-503. doi: 10.1097/ALN.0000000000000101
[26]	KIM SK, BAE H. Acupuncture and immune modulation[J]. Autonom Neurosc Basic Clin, 2010, 157(1/2) : 38-41. http://www.ncbi.nlm.nih.gov/pubmed/20399151
[27]	HAN JS. Acupuncture: Neuropeptide release produced by electrical stimulation of different frequencies[J ]. Trends Neurosci, 2003, 26(1) : 17-22. doi: 10.1016/S0166-2236(02)00006-1
[28]	MOLYNEAUX BJ, ARLOTTA P, MENEZES JR, et al. Neuronal subtype specification in the cerebral cortex[J]. Nat Rev Neurosci, 2007, 8(6) : 427-437. doi: 10.1038/nrn2151
[29]	HOCHBERG LR. Intracortical brain-computer interfaces for the restoration of communication and mobility[J]. Biophys J, 2013, 104(2) : 376. http://www.onacademic.com/detail/journal_1000035856305810_ffa6.html
[30]	CAJIGAS I, VEDANTAM A. Brain-computer interface, neuromodulation, and neurorehabilitation strategies for spinal cord injury[J]. Neurosurg Clin N Am, 2021, 32(3) : 407-417. doi: 10.1016/j.nec.2021.03.012
[31]	WEN D, FAN Y, HSU SH, etal. Combining brain-computer interface and virtual reality for rehabilitation in neurological diseases: A narrative review[J ]. Ann Phys Rehabil Med, 2021, 64(1) : 101404. doi: 10.1016/j.rehab.2020.03.015