Neural networks underlying impaired information gating in major depression

重度抑郁症中信息门控受损的神经网络

• 批准号: 8770624
• 负责人: IAN H GOTLIB
• 金额: $ 24.08万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-04 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8770624
• 关键词: Address; Affect; Affective; Attention; Attention deficit hyperactivity disorder; Attentional deficit; Behavior; Behavioral; Biological Assay; Biological Neural Networks; Bipolar Disorder; Brain; Cereals; Characteristics; Clinical; Cognitive; Corpus striatum structure; Data; Development; Disease; Dorsal; Economic Burden; Emotional; Emotions; Excision; Exhibits; Functional Magnetic Resonance Imaging; Goals; High Prevalence; Impairment; Individual; Individual Differences; Intervention; Knowledge; Lead; Maintenance; Major Depressive Disorder; Measures; Mental Depression; Modeling; Nature; Neurocognitive; Neurophysiology - biologic function; Participant; Patients; Pattern; Population; Prefrontal Cortex; Prevalence; Process; Research; Research Personnel; Scanning; Schizophrenia; Severities; Short-Term Memory; Stimulus; System; Techniques; Testing; Theoretical model; Training; Variant; Work; base; cost; depressive symptoms; effective intervention; improved; indexing; innovation; network models; neuroimaging; neuromechanism; novel; programs; public health relevance; relating to nervous system; research study; social; treatment strategy; visual memory; Address; Affect; Affective; Attention; Attention deficit hyperactivity disorder; Attentional deficit; Behavior; Behavioral; Biological Assay; Biological Neural Networks; Bipolar Disorder; Brain; Cereals; Characteristics; Clinical; Cognitive; Corpus striatum structure; Data; Development; Disease; Dorsal; Economic Burden; Emotional; Emotions; Excision; Exhibits; Functional Magnetic Resonance Imaging; Goals; High Prevalence; Impairment; Individual; Individual Differences; Intervention; Knowledge; Lead; Maintenance; Major Depressive Disorder; Measures; Mental Depression; Modeling; Nature; Neurocognitive; Neurophysiology - biologic function; Participant; Patients; Pattern; Population; Prefrontal Cortex; Prevalence; Process; Research; Research Personnel; Scanning; Schizophrenia; Severities; Short-Term Memory; Stimulus; System; Techniques; Testing; Theoretical model; Training; Variant; Work; base; cost; depressive symptoms; effective intervention; improved; indexing; innovation; network models; neuroimaging; neuromechanism; novel; programs; public health relevance; relating to nervous system; research study; social; treatment strategy; visual memory

DESCRIPTION (provided by applicant): A behavioral hallmark of Major Depressive Disorder (MDD) is impaired gating of negative, task-irrelevant information. In previous work we documented that people with MDD exhibit impairments in controlling the entry of irrelevant negative information into working memory (WM) and in removing no-longer-relevant information from WM. Given the high prevalence and enormous costs of MDD, it is critical that we gain a better under- standing of the neural mechanisms that underlie these cognitive difficulties. Although investigators have begun to examine neural correlates of impaired information-gating processes in MDD, we do not yet understand the functional significance of these activations or the nature of their relation to depression, or consequently, how to leverage this knowledge to develop and evaluate individualized treatments for this heterogeneous disorder. We propose to use cutting-edge neuroimaging techniques to elucidate the neural mechanisms that underlie impaired gating of negative information in MDD, conducting innovative analyses of fMRI data (multi-voxel pattern analyses [MVPA] and functional connectivity) in order to quantify on a moment-to-moment basis the degree to which negative irrelevant information is represented in WM. This approach will allow us to test hypotheses about (a) specific large-scale networks that are posited to underlie information-gating deficits in MDD; and (b) the contribution of these networks to various clinical characteristics of MDD. Specifically, in two experiments we will elucidate the cognitive and neural mechanisms that underlie impaired gating in MDD during the entry of negative stimuli into WM, and during the removal of negative information from WM. Moreover, given findings in nondepressed populations that individual differences in the ability to gate task- irrelevant information are related to variations in goal-directed behavior, we further propose to assess the relation of individual differences in information gating to specific aspects of depressive symptomatology. We hypothesize that impaired gating of negative irrelevant information in MDD is associated with anomalous functioning of dorsal frontoparietal (top-down attentional control) and subcortical (emotional appraisal) networks during both the entry of negative information into WM and the removal of negative information from WM. We further hypothesize that these abnormalities are related to the specific depressive characteristics of emotion dysregulation, rumination, and negative affect, and to the severity of depressive symptoms. Importantly, our novel quantification of neural representations of negative information will move beyond coarse group-level assays to a more fine-grained individual-subject and trial-level understanding of the dynamic nature of the neurocognitive mechanisms that underlie MDD. Together, the proposed studies promise to 1) advance understanding of mechanisms that underlie the control of affective information in MDD; 2) inform theoretical models of the interaction of attention and emotion; and 3) facilitate the ultimate development of more effective, patient-specific interventions (e.g., cognitive or neural training) for major depression.

描述（由申请人提供）：重度抑郁症（MDD）的行为标志是负面的，任务 - 息肉信息的门控。在先前的工作中，我们记录了具有MDD的人在控制无关的负面信息（WM）以及从WM中删除不相关的信息时表现出障碍。鉴于MDD的高流行和巨大成本，至关重要的是，我们可以更好地了解这些认知困难的神经机制。尽管研究人员已经开始检查MDD中信息门控过程受损的神经相关性，但我们尚未了解这些激活的功能意义或它们与抑郁症关系的性质，或者因此如何利用这种知识来开发和评估这种异质性疾病的个性化治疗方法。我们建议使用最先进的神经影像学技术来阐明MDD中负面信息门控障碍的神经机制，对fMRI数据进行创新分析（多素素模式分析[MVPA]和功能连接），以便在矩之间量化，以量化无效的信息。这种方法将使我们能够测试有关（a）被认为是MDD中信息门控赤字的特定大规模网络的假设； （b）这些网络对MDD的各种临床特征的贡献。具体而言，在两个实验中，我们将阐明在将负刺激进入WM期间以及从WM中删除负面信息期间，MDD的门控受损的认知和神经机制。此外，考虑到不抑郁的人群中的发现，即将到达任务的能力的个体差异与目标指导行为的差异有关，我们进一步建议评估信息门控在抑郁症状学特定方面的个体差异的关系。我们假设MDD中负相关信息的门控障碍与背侧额叶（自上而下的注意力控制）和皮层（情绪评估）网络的异常功能有关，这两种网络都将负面信息输入WM以及从WM中删除负面信息。我们进一步假设这些异常与情绪失调，反省和负面影响的特定抑郁特征以及抑郁症状的严重程度有关。重要的是，我们对阴性信息神经表示的新颖量化将超越粗群级别的测定法，以对基于MDD的神经认知机制的动态性质进行更细粒度的个人主体和试验级别的理解。拟议的研究共同承诺1）提前了解MDD中情感信息控制的机制； 2）向理论模型告知注意力与情感的相互作用； 3）促进对重度抑郁症的更有效，特定于患者的干预措施（例如认知或神经训练）的最终发展。