Fingelkurts Al A, Fingelkurts An A
BM-Science - Brain and Mind Technologies Research Centre, Espoo, Finland.
Open Neuroimag J. 2010 Sep 8;4:111-3. doi: 10.2174/1874440001004010111.
An electroencephalogram (EEG) signal is extremely nonstationary, highly composite and very complex, all of which reflects the underlying integral neurodynamics. Understanding the EEG "grammar", its internal structural organization would place a "Rozetta stone" in researchers' hands, allowing them to more adequately describe the information processes of the brain in terms of EEG phenomenology. This Special Issue presents a framework where short-term EEG spectral pattern (SP) of a particular type is viewed as an information-rich event in EEG phenomenology. It is suggested that transition from one type of SP to another is accompanied by a "switch" between brain microstates in specific neuronal networks, or in cortex areas; and these microstates are reflected in EEG as piecewise stationary segments. In this context multiple faces of a short-term EEG SP reflect the poly-operational structure of brain activity.
脑电图（EEG）信号极不稳定、高度复合且非常复杂，所有这些都反映了潜在的整体神经动力学。理解脑电图的“语法”，即其内部结构组织，将为研究人员提供一块“罗塞塔石碑”，使他们能够根据脑电图现象学更充分地描述大脑的信息处理过程。本期特刊提出了一个框架，其中特定类型的短期脑电图频谱模式（SP）被视为脑电图现象学中一个信息丰富的事件。有人认为，从一种类型的SP转换到另一种类型伴随着特定神经网络或皮层区域中脑微状态之间的“切换”；而这些微状态在脑电图中表现为分段平稳段。在这种情况下，短期脑电图SP的多面性反映了大脑活动的多操作结构。
