Integrating EEG/MEG and fMRI: 99-M-0172

整合 EEG/MEG 和 fMRI：99-M-0172

• 批准号: 8342165
• 负责人: Richard Coppola
• 金额: $ 8.73万
• 依托单位: NATIONAL INSTITUTE OF MENTAL HEALTH
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8342165
• 关键词: Address; Amygdaloid structure; Anterior; Area; Auditory; Awareness; Behavioral; Brain; Brain Part; Brain region; Clinical; Cognitive; Cognitive deficits; Cognitive remediation; Coupling; Data; Development; Disease; Electroencephalography; Family member; Functional Magnetic Resonance Imaging; Functional disorder; Genetic; Genotype; Imaging Techniques; Impaired cognition; Individual Differences; Investigation; Measurement; Measures; Memory; Methods; Neurons; Outcome; Pathology; Patients; Pattern; Performance; Phenotype; Pilot Projects; Prefrontal Cortex; Process; Protocols documentation; Resolution; Rest; Schizophrenia; Short-Term Memory; Siblings; Signal Transduction; Source; Structure; Susceptibility Gene; System; Task Performances; Techniques; Time; Training; Visual; Work; base; cingulate cortex; computerized data processing; gamma-Aminobutyric Acid; genetic association; improved; indexing; information processing; neuropsychiatry; patient population; remediation; response; tool; trait; volunteer

Development of MEG data recording and signal processing methods has been very successful. Studies of working memory tasks and auditory processing tasks have shown the ability to localize brain activation and to address issues of phasic versus tonic activity. We are investigating phenotype measures that will be applicable in many related studies and specifically the sibling project. MEG recording during cognitive activation has shown the ability to localize in very comparable fashion to fMRI. Specifically beta desynchronization at the cortical level has been found to agree with BOLD activation results. However, the MEG/EEG allows for temporal information not possible with other imaging techniques. Phasic relationships across brain areas have been demonstrated using advanced signal processing techniques. Our results show that measures of brain structure and function represent powerful tools to find susceptibility genes. Further studies have demonstrated the ability to localize signals in deeper structures such as the amygdala and to investigate the relation of visual awareness to gamma band signals. We have also found that GABA (gamma-aminobutyric acid) concentration in the anterior cingulate cortex correlates with spatially localized resting MEG beta band power. We expect that further investigation will reveal addtional relationships between gamma power and GABA systems. Diffrerences in the degree of activation especially in frontal regions as indexed by beta desynchronization during a working memory task have been found between patients with schizophrenia compared to well siblings and normal control volunteers. Further investigation of this activation has revealed an interaction with genotype for the well studied COMT marker. We have found there is a modulation of prefrontal cortex activity that occurs in anticipation of the upcoming task demands. This preparatory signal may be important in investigating cognitive dysfunction in patient populations. Differences in network patterns and dynamics are key to understanding underlying pathology in clinical groups. Bassett et al have shown that functional network differences in patient groups can be demonstrated and related to behavioral outcomes on cognitive activities. Rutter et al have shown that even at rest patients with schizophrenia have gamma power reduction compared to normal subjects. It remains to be seen whether these finding relate to state or trait differences and if there are genetic associations. We have found distinct patterns of the temporal sequence of brain regions involved in these memory tasks that show a variety of individual differences across subjects. These differences will form the basis for genotypic patterns and dscrimination in patient groups. Recent work has sought to examine whether reorganization of functional brain networks can be seen in response to cognitive remediation strategies. A pilot study of MEG recorded before and after auditory task training addressed this question. We were able to show significant changes in power and coherence in brain activity that were asociated with improved behavioral performance. This could form the basis for developing remediation strategies targeting specific cognitive deficits in neuropsychiatric disorders.

MEG数据记录和信号处理方法的开发非常成功。对工作记忆任务和听觉处理任务的研究表明，能够定位大脑激活并解决阶段性活动与补品活动的问题。我们正在研究将适用于许多相关研究，特别是同级项目的表型测量。 认知激活期间的MEG记录表明能够以与fMRI相当的方式定位。已发现皮质水平上的beta脱离同步与大胆的激活结果一致。但是，MEG/EEG允许使用其他成像技术提供时间信息。已经使用高级信号处理技术证明了整个大脑区域的阶段关系。我们的结果表明，大脑结构和功能的度量代表了找到敏感基因的强大工具。进一步的研究表明，可以将信号定位在杏仁核等更深的结构中，并研究视觉意识与伽马频带信号的关系。我们还发现，前扣带回皮层中的GABA（γ-氨基丁酸）浓度与空间局部静止的MEGβ带功率相关。我们预计进一步的调查将揭示伽马功率与GABA系统之间的添加关系。 与兄弟姐妹和正常的对照志愿者相比，精神分裂症患者之间在工作记忆任务期间，在工作记忆任务期间通过Beta Denchronation在工作记忆任务期间通过Beta Denchronation指数的额叶区域的衍射。对这种激活的进一步研究揭示了研究良好的COMT标记与基因型的相互作用。我们发现，在预期即将到来的任务需求的情况下，发生了前额叶皮层活动的调节。该预备信号对于研究患者人群的认知功能障碍可能很重要。 网络模式和动态的差异是理解临床组潜在病理的关键。 Bassett等人表明，可以证明患者组的功能网络差异，并与认知活动的行为结果有关。 Rutter等人表明，即使在精神分裂症患者中，与正常受试者相比，即使在精神分裂症患者中，也具有伽马功率的降低。这些发现是否与状态差异或性格差异以及是否存在遗传关联有关还有待观察。我们发现了这些记忆任务中涉及的大脑区域的时间顺序的不同模式，这些模式显示了各个受试者的各种个体差异。这些差异将构成患者群体中基因型模式和差异的基础。 最近的工作试图检查是否可以根据认知补救策略进行功能性脑网络的重组。在听觉任务培训训练之前和之后记录了对MEG的试点研究解决了这个问题。我们能够显示出与行为表现改善的大脑活动的功率和连贯性的显着变化。这可能是制定针对神经精神疾病中特定认知缺陷的补救策略的基础。