Lehmann D
Department of Neurology, University Hospital, Zurich, Switzerland.
Brain Topogr. 1990 Fall;3(1):191-202. doi: 10.1007/BF01128876.
Traditional EEG and EP analysis is trace-oriented. When mapping became popular, results of waveform analysis were mapped. Increased exposure to brain field maps has begun to orient analysis to the spatial aspects. Different maps must be generated by different neuronal populations; this offers direct key to the analysis of higher brain function. Space-oriented data reduction selects maps with optimal signal/noise ratio using Global Dissimilarity index. Classification and statistics of map landscapes uses extracted descriptors (locations of extrema or centroids) or three-dimensional dipole models. Map classification leads to adaptive segmentation of evoked or spontaneous map series into functional micro-states, the putative building blocks of perception and cognition.
传统的脑电图（EEG）和诱发电位（EP）分析是以波形为导向的。当脑图谱变得流行起来后，波形分析的结果被映射出来。对脑电场图谱的更多接触已开始使分析转向空间方面。不同的图谱必须由不同的神经元群体生成；这为分析高级脑功能提供了直接的关键线索。面向空间的数据约简使用全局差异指数来选择具有最佳信噪比的图谱。图谱景观的分类和统计使用提取的描述符（极值或质心的位置）或三维偶极子模型。图谱分类会将诱发或自发的图谱序列自适应分割为功能性微状态，这些微状态被认为是感知和认知的构建模块。
