{"title":"疼痛与大脑:方法、脑电图生物标记物、局限性和未来方向的系统回顾。","authors":"Bayan Ahmad, Buket D Barkana","doi":"10.3390/neurolint17040046","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background:</b> Pain is prevalent in almost all populations and may often hinder visual, auditory, tactile, olfactory, and taste perception as it alters brain neural processing. The quantitative methods emerging to define pain and assess its effects on neural functions and perception are important. Identifying pain biomarkers is one of the initial stages in developing such models and interventions. The existing literature has explored chronic and experimentally induced pain, leveraging electroencephalograms (EEGs) to identify biomarkers and employing various qualitative and quantitative approaches to measure pain. <b>Objectives</b>: This systematic review examines the methods, participant characteristics, types of pain states, associated pain biomarkers of the brain's electrical activity, and limitations of current pain studies. The review identifies what experimental methods researchers implement to study human pain states compared to human control pain-free states, as well as the limitations in the current techniques of studying human pain states and future directions for research. <b>Methods</b>: The research questions were formed using the Population, Intervention, Comparison, Outcome (PICO) framework. A literature search was conducted using PubMed, PsycINFO, Embase, the Cochrane Library, IEEE Explore, Medline, Scopus, and Web of Science until December 2024, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines to obtain relevant studies. The inclusion criteria included studies that focused on pain states and EEG data reporting. The exclusion criteria included studies that used only MEG or fMRI neuroimaging techniques and those that did not focus on the evaluation or assessment of neural markers. Bias risk was determined by the Newcastle-Ottawa Scale. Target data were compared between studies to organize the findings among the reported results. <b>Results</b>: The initial search resulted in 592 articles. After exclusions, 24 studies were included in the review, 6 of which focused on chronic pain populations. Experimentally induced pain methods were identified as techniques that centered on tactile perception: thermal, electrical, mechanical, and chemical. Across both chronic and stimulated pain studies, pain was associated with decreased or slowing peak alpha frequency (PAF). In the chronic pain studies, beta power increases were seen with pain intensity. The functional connectivity and pain networks of chronic pain patients differ from those of healthy controls; this includes the processing of experimental pain. Reportedly small sample sizes, participant comorbidities such as neuropsychiatric disorders and peripheral nerve damage, and uncontrolled studies were the common drawbacks of the studies. Standardizing methods and establishing collaborations to collect open-access comprehensive longitudinal data were identified as necessary future directions to generalize neuro markers of pain. <b>Conclusions</b>: This review presents a variety of experimental setups, participant populations, pain stimulation methods, lack of standardized data analysis methods, supporting and contradicting study findings, limitations, and future directions. Comprehensive studies are needed to understand the pain and brain relationship deeper in order to confirm or disregard the existing findings and to generalize biomarkers across chronic and experimentally induced pain studies. This requires the implementation of larger, diverse cohorts in longitudinal study designs, establishment of procedural standards, and creation of repositories. Additional techniques include the utilization of machine learning and analyzing data from long-term wearable EEG systems. The review protocol is registered on INPLASY (# 202520040).</p>","PeriodicalId":19130,"journal":{"name":"Neurology International","volume":"17 4","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12029872/pdf/","citationCount":"0","resultStr":"{\"title\":\"Pain and the Brain: A Systematic Review of Methods, EEG Biomarkers, Limitations, and Future Directions.\",\"authors\":\"Bayan Ahmad, Buket D Barkana\",\"doi\":\"10.3390/neurolint17040046\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b>Background:</b> Pain is prevalent in almost all populations and may often hinder visual, auditory, tactile, olfactory, and taste perception as it alters brain neural processing. The quantitative methods emerging to define pain and assess its effects on neural functions and perception are important. Identifying pain biomarkers is one of the initial stages in developing such models and interventions. The existing literature has explored chronic and experimentally induced pain, leveraging electroencephalograms (EEGs) to identify biomarkers and employing various qualitative and quantitative approaches to measure pain. <b>Objectives</b>: This systematic review examines the methods, participant characteristics, types of pain states, associated pain biomarkers of the brain's electrical activity, and limitations of current pain studies. The review identifies what experimental methods researchers implement to study human pain states compared to human control pain-free states, as well as the limitations in the current techniques of studying human pain states and future directions for research. <b>Methods</b>: The research questions were formed using the Population, Intervention, Comparison, Outcome (PICO) framework. A literature search was conducted using PubMed, PsycINFO, Embase, the Cochrane Library, IEEE Explore, Medline, Scopus, and Web of Science until December 2024, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines to obtain relevant studies. The inclusion criteria included studies that focused on pain states and EEG data reporting. The exclusion criteria included studies that used only MEG or fMRI neuroimaging techniques and those that did not focus on the evaluation or assessment of neural markers. Bias risk was determined by the Newcastle-Ottawa Scale. Target data were compared between studies to organize the findings among the reported results. <b>Results</b>: The initial search resulted in 592 articles. After exclusions, 24 studies were included in the review, 6 of which focused on chronic pain populations. Experimentally induced pain methods were identified as techniques that centered on tactile perception: thermal, electrical, mechanical, and chemical. Across both chronic and stimulated pain studies, pain was associated with decreased or slowing peak alpha frequency (PAF). In the chronic pain studies, beta power increases were seen with pain intensity. The functional connectivity and pain networks of chronic pain patients differ from those of healthy controls; this includes the processing of experimental pain. Reportedly small sample sizes, participant comorbidities such as neuropsychiatric disorders and peripheral nerve damage, and uncontrolled studies were the common drawbacks of the studies. Standardizing methods and establishing collaborations to collect open-access comprehensive longitudinal data were identified as necessary future directions to generalize neuro markers of pain. <b>Conclusions</b>: This review presents a variety of experimental setups, participant populations, pain stimulation methods, lack of standardized data analysis methods, supporting and contradicting study findings, limitations, and future directions. Comprehensive studies are needed to understand the pain and brain relationship deeper in order to confirm or disregard the existing findings and to generalize biomarkers across chronic and experimentally induced pain studies. This requires the implementation of larger, diverse cohorts in longitudinal study designs, establishment of procedural standards, and creation of repositories. Additional techniques include the utilization of machine learning and analyzing data from long-term wearable EEG systems. The review protocol is registered on INPLASY (# 202520040).</p>\",\"PeriodicalId\":19130,\"journal\":{\"name\":\"Neurology International\",\"volume\":\"17 4\",\"pages\":\"\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12029872/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neurology International\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/neurolint17040046\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neurology International","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/neurolint17040046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
摘要
背景:疼痛在几乎所有人群中都很普遍,并且通常会阻碍视觉、听觉、触觉、嗅觉和味觉的感知,因为它改变了大脑的神经处理过程。定义疼痛和评估其对神经功能和感知的影响的定量方法是重要的。识别疼痛生物标志物是开发此类模型和干预措施的初始阶段之一。现有文献探讨了慢性和实验性疼痛,利用脑电图(eeg)来识别生物标志物,并采用各种定性和定量方法来测量疼痛。目的:本系统综述探讨了方法、参与者特征、疼痛状态类型、脑电活动相关的疼痛生物标志物以及当前疼痛研究的局限性。本文综述了研究人员在研究人类疼痛状态和人类无疼痛状态时采用的实验方法,以及目前研究人类疼痛状态技术的局限性和未来的研究方向。方法:采用人口、干预、比较、结果(PICO)框架形成研究问题。文献检索使用PubMed、PsycINFO、Embase、Cochrane Library、IEEE Explore、Medline、Scopus和Web of Science,检索时间截止到2024年12月,文献检索遵循PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis)指南获取相关研究。纳入标准包括关注疼痛状态和脑电图数据报告的研究。排除标准包括仅使用MEG或fMRI神经成像技术的研究,以及不侧重于评估或评估神经标志物的研究。偏倚风险由纽卡斯尔-渥太华量表确定。对研究间的目标数据进行比较,在已报道的结果中整理研究结果。结果:最初的搜索结果是592篇文章。排除后,纳入了24项研究,其中6项关注慢性疼痛人群。实验诱导疼痛的方法被确定为以触觉感知为中心的技术:热的、电的、机械的和化学的。在慢性疼痛和刺激疼痛的研究中,疼痛与α峰频率(PAF)降低或减慢有关。在慢性疼痛研究中,随着疼痛强度的增加,β能量增加。慢性疼痛患者的功能连通性和疼痛网络与健康对照者不同;这包括对实验性疼痛的处理。据报道,样本量小、参与者合并症(如神经精神疾病和周围神经损伤)和未控制的研究是这些研究的常见缺点。标准化方法和建立合作来收集开放获取的综合纵向数据被认为是未来推广疼痛神经标志物的必要方向。结论:本文综述了各种实验设置、参与者人群、疼痛刺激方法、缺乏标准化的数据分析方法、支持和反对研究结果、局限性和未来方向。需要全面的研究来更深入地了解疼痛和大脑的关系,以证实或忽视现有的发现,并在慢性和实验诱导的疼痛研究中推广生物标志物。这需要在纵向研究设计中实现更大的、不同的队列,建立程序标准,并创建存储库。其他技术包括利用机器学习和分析长期可穿戴脑电图系统的数据。审查协议已在INPLASY(# 202520040)上注册。
Pain and the Brain: A Systematic Review of Methods, EEG Biomarkers, Limitations, and Future Directions.
Background: Pain is prevalent in almost all populations and may often hinder visual, auditory, tactile, olfactory, and taste perception as it alters brain neural processing. The quantitative methods emerging to define pain and assess its effects on neural functions and perception are important. Identifying pain biomarkers is one of the initial stages in developing such models and interventions. The existing literature has explored chronic and experimentally induced pain, leveraging electroencephalograms (EEGs) to identify biomarkers and employing various qualitative and quantitative approaches to measure pain. Objectives: This systematic review examines the methods, participant characteristics, types of pain states, associated pain biomarkers of the brain's electrical activity, and limitations of current pain studies. The review identifies what experimental methods researchers implement to study human pain states compared to human control pain-free states, as well as the limitations in the current techniques of studying human pain states and future directions for research. Methods: The research questions were formed using the Population, Intervention, Comparison, Outcome (PICO) framework. A literature search was conducted using PubMed, PsycINFO, Embase, the Cochrane Library, IEEE Explore, Medline, Scopus, and Web of Science until December 2024, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines to obtain relevant studies. The inclusion criteria included studies that focused on pain states and EEG data reporting. The exclusion criteria included studies that used only MEG or fMRI neuroimaging techniques and those that did not focus on the evaluation or assessment of neural markers. Bias risk was determined by the Newcastle-Ottawa Scale. Target data were compared between studies to organize the findings among the reported results. Results: The initial search resulted in 592 articles. After exclusions, 24 studies were included in the review, 6 of which focused on chronic pain populations. Experimentally induced pain methods were identified as techniques that centered on tactile perception: thermal, electrical, mechanical, and chemical. Across both chronic and stimulated pain studies, pain was associated with decreased or slowing peak alpha frequency (PAF). In the chronic pain studies, beta power increases were seen with pain intensity. The functional connectivity and pain networks of chronic pain patients differ from those of healthy controls; this includes the processing of experimental pain. Reportedly small sample sizes, participant comorbidities such as neuropsychiatric disorders and peripheral nerve damage, and uncontrolled studies were the common drawbacks of the studies. Standardizing methods and establishing collaborations to collect open-access comprehensive longitudinal data were identified as necessary future directions to generalize neuro markers of pain. Conclusions: This review presents a variety of experimental setups, participant populations, pain stimulation methods, lack of standardized data analysis methods, supporting and contradicting study findings, limitations, and future directions. Comprehensive studies are needed to understand the pain and brain relationship deeper in order to confirm or disregard the existing findings and to generalize biomarkers across chronic and experimentally induced pain studies. This requires the implementation of larger, diverse cohorts in longitudinal study designs, establishment of procedural standards, and creation of repositories. Additional techniques include the utilization of machine learning and analyzing data from long-term wearable EEG systems. The review protocol is registered on INPLASY (# 202520040).