Face Affect Processing in Schizophrenia with MEG

使用 MEG 处理精神分裂症的面部情感

• 批准号: 6872807
• 负责人: STEPHEN F LEWIS
• 金额: $ 11.89万
• 依托单位: BIOMEDICAL RESEARCH INSTITUTE OF NEW MEX
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-03-15 至 2007-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6872807
• 关键词: adult human (21+); amygdala; behavioral /social science research tag; bioimaging /biomedical imaging; brain electrical activity; brain mapping; cingulate gyrus; clinical research; computer program /software; emotions; face expression; human subject; interview; magnetoencephalography; method development; neural information processing; neuropathology; neuropsychological tests; quality of life; questionnaires; schizophrenia; temporal lobe /cortex; visual cortex

DESCRIPTION (provided by applicant): Our group has begun development of MEG data analysis methods to better describe neural mechanisms involved in the deficits in recognition of emotional facial expressions in schizophrenia. Our model is derived from the existing literature, and from pilot work done in our lab using MEG neuroimaging techniques in both patients with schizophrenia and normal controls performing facial affect recognition tasks. We hypothesize (1) between-group differences in MEG-assessed brain activation in specific brain regions and (2) a critical role for those deficits in the cognitive and social dysfunction seen in schizophrenia. Our lab has successfully localized three distinct dipolar sources during facial affect processing. We propose to further investigate MEG-assessed face emotion information processing abnormalities and their relation to behavioral measures. We will test for differences between groups on MEG measures in a brain region associated with general visual processing general (V1, calcarine cortex), a brain region specialized for processing faces (fusiform gyrus), a brain region implicated in assessment of emotional content (amygdala), and a brain region that attends to salient environmental features (anterior cingulate gyrus). MEG analysis will be done concurrently using Neuromag software for comparison with the existing literature and with our Multi Start Spatio-Temporal dipole modeling to develop new techniques. We will also generate a method for assessing the connectivity between these brain areas using a mutual information exchange calculation. MEG analyses will be related to (1) an affect processing battery, (2) standard symptom scales, and (3) measures of quality of life for subjects with schizophrenia.

描述（由申请人提供）：我们的小组已经开始开发MEG数据分析方法，以更好地描述缺陷中涉及的神经机制，以识别精神分裂症的情绪面部表情。我们的模型源自现有文献，以及在精神分裂症患者中使用MEG神经影像学技术在实验室中进行的试验工作，并且执行面部影响识别任务的正常对照组。我们假设（1）特定大脑区域中MEG评估的大脑激活的组间差异，以及（2）这些缺陷在精神分裂症中所见的认知和社会功能障碍中的关键作用。 在面部影响处理过程中，我们的实验室已成功定位了三个不同的偶极源。我们建议进一步研究MEG评估的面部情绪信息处理异常及其与行为措施的关系。我们将测试与一般视觉处理通用（V1，Calcarine Cortex）相关的MEG测量组之间的差异，该大脑区域（V1，Calcarine Cortex）是一个专门用于处理面孔的大脑区域（Fusiform Gyrus），这是一个涉及评估情绪含量（Amygdala）的大脑区域（Amygdala），并且大脑区域与明智的环境特征（Earterior cisterior Cipcits cistrus ciss cistrus）一起参加。 MEG分析将使用Neuromag软件同时进行，以与现有文献进行比较，并与我们的多开始时空偶极偶极偶极子建模来开发新技术。我们还将通过使用共同信息交换计算来评估这些大脑区域之间的连通性的方法。 MEG分析将与（1）影响处理电池，（2）标准症状量表以及（3）精神分裂症受试者的生活质量度量有关。