Dynamic Neuroimaging with High-resolution SSVEPs

描述：拟议的实验、模拟和理论脑电研究将开发现代工程工具，供认知和医学科学家未来使用。这些工具可能适用于各种疾病状态，包括精神障碍(ADHD、抑郁症、精神分裂症、抑郁症、睡眠障碍等)。以及神经疾病(癫痫、头部创伤、中风、昏迷、阿尔茨海默病等)。提出的工具结合了高分辨率脑电和脑磁图，以及新的方法来量化脑电和稳态视觉诱发电位(SSVEP)的动态(时空)特性。实验研究将应用高分辨率SSVEP动态测量来研究意识知觉、选择性注意、知觉组织和工作记忆。将开发确定皮质区域之间功能整合的真正测量的方法，并使用高分辨率SSVEP进行测试。SSVEP提供了在很大程度上没有伪影的新皮质动态和认知功能的稳健测量。功能本地化与集成化之间竞争的SSVEP措施将包括不同频段的相干和其他锁相措施。实验中的SSVEP数据将在“突触作用场”背景下的细胞组装形成的背景下使用基于真实生理学和解剖学的新皮质动态功能理论模型来解释。突触作用场被定义为任何时间活跃的兴奋性突触和抑制性突触的数量密度，与功能无关。这一理论结构提供了生理学与EEG/SSVEP数据之间的必要联系。以这种方式，将获得脑电动力学、认知过程和理论模型之间的三重对应。在这些研究中开发的EEG和SSVEP工具应该为以后应用于广泛的特定认知或医学条件的研究提供坚实的基础。这些工具将作为用于高分辨率EEG、SSVEP和MEG分析的软件免费分发，并附带辅助手册和示例

DESCRIPTION: The proposed experimental, simulation, and theoretical EEG studies will develop modern engineering tools for future use by cognitive and medical scientists. These tools are potentially applicable to a wide variety of disease states, including mental disorders (ADHD, depression, schizophrenia, depression, sleep disorders, etc.) and neurological conditions (epilepsies, head trauma, strokes, coma, Alzheimer's disease, etc.). The proposed tools combine high-resolution EEG with MEG and new methods to quantify dynamic (spatial-temporal) properties of EEG and steady-state visually evoked potentials (SSVEP). Experimental studies will apply high-resolution SSVEP dynamic measures to investigate conscious perception, selective attention, perceptual organization, and working memory. Methods to identify genuine measures of functional integration between cortical areas will be developed and tested with high-resolution SSVEP. SSVEP provides robust measures of neocortical dynamic and cognitive function that are largely artifact-free. SSVEP measures of the "competition" between functional localization and integration will include coherence and other phase locking measures in various frequency bands. The experimental SSVEP data will be interpreted in the context of cell assembly formation embedded within a background of "synaptic action fields" using theoretical models of neocortical dynamic function based on genuine physiology and anatomy. The synaptic action fields are defined as the number densities of active excitatory and inhibitory synapses at any time, independent of function. This theoretical construct provides the necessary connection between physiology and EEG/SSVEP data. In this manner, a triple correspondence between EEG dynamics, cognitive processes, and theoretical models will be obtained. The EEG and SSVEP tools developed in these studies should provide firm foundations for later studies applied to a wide range of specific cognitive or medical conditions. These tools will be freely distributed as software for high-resolution EEG, SSVEP, and MEG analysis with a supporting manual and examples