从病床到桌面：规范性颅内脑电图与异常映射的数据协议
From Bedside to Desktop: A Data Protocol for Normative Intracranial EEG and Abnormality Mapping
AI总结：
针对颅内脑电图缺乏规范性图谱构建标准化流程的问题，本研究提出一套汇总现有方法的数据流协议，可生成脑区定位的icEEG常模图谱并实现异常映射，已在12篇论文中应用，有望提升领域研究一致性。
摘要：
规范性映射是一种用于绘制健康相关变量群体水平特征的框架，在神经科学研究中应用广泛，但现有文献在颅内脑电图（icEEG）等无法开展健康对照测量的模态中，缺乏成熟的操作协议。icEEB规范性图谱可帮助研究者了解群体水平的大脑活动，还能将个体数据与这些常模对比以识别异常。目前，尚无将临床数据转化为区域性icEEG规范性图谱的标准化指南。相关论文往往引用不同软件和大量文献来阐述这一冗长的方法流程，导致其他研究者理解或应用该过程十分费力。我们的协议旨在通过提供汇总现有方法的数据流指南和关键决策点，填补这一空白，该协议已在本实验室已发表的12篇同行评审期刊论文中大量使用。简而言之，我们以接受切除性手术评估的癫痫患者的icEEG记录和神经影像数据为输入，最终输出包含定位于脑区的信号特征的icEEG规范性图谱。此外，我们还可通过同一流程处理新受试者，获取其每个脑区的z分数（或百分位数），用于异常检测与定位。截至目前，尚未有一套用于生成icEEG规范性图谱并开展异常映射的完整统一数据流流程。我们预计，该数据流指南不仅将增进对规范性映射方法的理解与应用，还将提升该领域研究的一致性与质量。
英文摘要：
Normative mapping is a framework used to map population-level features of health-related variables. It is widely used in neuroscience research, but the literature lacks established protocols in modalities that do not support healthy control measurements, such as intracranial EEG (icEEG). An icEEG normative map would allow researchers to learn about population-level brain activity and enable comparison of individual data against these norms to identify abnormalities. Currently, no standardised guide exists for transforming clinical data into a normative, regional icEEG map. Papers often cite different software and numerous articles to summarise the lengthy method, making it laborious for other researchers to understand or apply the process. Our protocol seeks to remedy this gap by providing a dataflow guide and key decision points that summarise existing methods. This protocol is used heavily in published works from our own lab (twelve peer-reviewed journal publications). Briefly, we take as input, icEEG recordings and neuroimaging data from people with epilepsy who are undergoing evaluation for resective surgery. As final outputs, we obtain a normative icEEG map, comprising signal properties localised to brain regions. Optionally, we can also process new subjects through the same pipeline and obtain their z-scores (or centiles) in each brain region, for abnormality detection and localisation. To date, a single, cohesive, dataflow pipeline for generating normative icEEG maps, along with abnormality mapping, has not been created. We envisage that this dataflow guide will not only increase understanding and application of normative mapping methods, but will also improve the consistency and quality of studies in the field.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
