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，以更好地描述精神分裂症情绪面部表情识别缺陷所涉及的神经机制。我们的模型源自现有文献，以及我们实验室使用 MEG 神经成像技术对精神分裂症患者和正常对照执行面部情感识别任务进行的试点工作。我们假设（1）特定大脑区域的 MEG 评估的大脑激活存在组间差异，以及（2）这些缺陷在精神分裂症的认知和社会功能障碍中发挥着关键作用。 我们的实验室在面部情感处理过程中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测量的关系。我们将测试各组之间在与一般视觉处理相关的大脑区域（V1，距状皮层）、专门处理面部的大脑区域（梭状回）、与情绪内容评估有关的大脑区域（杏仁核）的 MEG 测量值上的差异。 ），以及负责显着环境特征的大脑区域（前扣带回）。 MEG 分析将同时使用 Neuromag 软件进行，以便与现有文献进行比较，并与我们的多启动时空偶极子模型进行比较，以开发新技术。我们还将生成一种使用相互信息交换计算来评估这些大脑区域之间的连接性的方法。 MEG 分析将与 (1) 情感处理电池、(2) 标准症状量表和 (3) 精神分裂症受试者的生活质量测量相关。