Effect of Mood on Cognition: A Neuropsychometric Approach to Brain Imaging

描述（由申请人提供）：拟议研究的目标是更好地了解自我评价认知的情绪约束的大脑机制。我们提出了一种新的神经心理测量方法，试图合并心理测量的优势（即，情绪状态的测量）与时间敏感性密集阵列脑电图（dEEG）。我们还利用dEEG源分析的进展，以便在神经解剖学的背景下的结果。这种方法不仅有助于解释结果，还使我们能够更直接地测试临床神经科学文献中提出的情感和认知大脑过程的模型。一个二维的情绪模型（积极情绪和消极情绪）有望解释差异的大脑活动在背内侧和腹外侧皮层网络相关的自我评价认知。 神经心理测量方法利用单字描述符的心理测量特性（例如，平静）以放大与积极情绪相关的dEEG中的方差 或负面影响。为每个描述项导出加权统计量，该加权统计量描述项与感兴趣的心理度量量表相关联的程度。在大脑成像过程中，健康的成年参与者评估每个单词自我描述的程度。然后根据描述符与PA和NA的关联分别对dEEG的单个试验进行加权。平均数据预计将反映自我评价认知的神经指标的心理测量维度的集中趋势。模拟的神经源活动将用于测试与适应不良自我评价（即抑郁）相关的脑功能模型。 该研究计划旨在帮助候选人在学术研究生涯的早期阶段取得进展。候选人寻求更好地了解精神病理学的大脑基础，并随后将这些知识用于开发和测量越来越有效的基于情绪的心理障碍治疗方法。 公共卫生相关性：该研究利用dEEG技术来研究健康成年人自我评价认知固有的情绪偏见。我们提出了一种新的神经心理测量方法，可能提供重要的方法学进展的研究情感约束的认知在大脑中。其目的是确定健康大脑中情绪偏见，自我评价过程的神经活动。研究结果可能表明，大脑功能模型可能与临床抑郁症的关键症状有关。

DESCRIPTION (provided by applicant): The goal of the proposed research is to better understand the brain mechanisms that underlie mood constraints on self-evaluative cognition. We propose a novel neuropsychometric approach to this study that attempts to merge the strengths of psychometric measurement (i.e., measurement of mood state) with the temporal sensitivity dense array electroencephalography (dEEG). We also utilize advances in dEEG source analysis in order to contextualize findings in neuroanatomy. This methodology not only aids in the interpretation of results by also enables us to more directly test models of affective and cognitive brain processes that have been suggest in the clinical neuroscience literature. A two-dimensional model of mood (Positive Affect and Negative Affect) is expected to explain differential brain activity in dorsal-medial and ventral-lateral cortical networks related to self-evaluative cognition. The neuropsychometric approach utilizes psychometric properties of single-word descriptors (e.g., calm) to amplify variance in dEEG that is related to Positive Affect or Negative Affect. A weighting statistic is derived for each descriptor item that describes the extent to which the item is associated with the psychometric scale of interest. During brain imaging, healthy, adult participants evaluate the extent to which each word is self- descriptive. Single trials of dEEG are then weighted according to the descriptor's association with PA and NA, respectively. Averaged data is expected to reflect the central tendency of the psychometric dimensions in neural indices of self-evaluative cognition. Modeled neural source activity will be used to test a model of brain function associated with maladaptive self-evaluation (i.e. depression). This research program is designed to assist the candidate's progress in the early stages of an academic research career. The candidate seeks to better understand the brain basis of psychopathology, and subsequently employ this knowledge in the development and measurement of increasingly efficacious treatments for mood-based psychological disorders. PUBLIC HEALTH RELEVANCE: The proposed research utilizes dEEG technology to investigate mood biases inherent to self-evaluative cognition in healthy adults. We propose a novel neuropsychometric approach that may provide important methodological advances in the study of affective constraint on cognition in the brain. The aim is to identify neural activity specific to mood biased, self-evaluative processes in the healthy brain. Results may suggest a model of brain function that can be associated with key symptoms of clinical depression.