Structural & Network-Function Correlates of Fragmented Early-Life Across Species

结构性

• 批准号: 9355809
• 负责人: Steven L Small
• 金额: --
• 依托单位: UNIVERSITY OF CALIFORNIA-IRVINE
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-06-17 至 2018-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9355809
• 关键词: Adolescence; Adolescent; Adolescent Behavior; Affect; Age; Anxiety; Area; Behavioral; Brain; Brain imaging; Brain region; Caring; Child; Childhood; Clinical; Cognitive; Complex; Data; Defect; Dendritic Spines; Development; Diffusion Magnetic Resonance Imaging; Disease; Emotional; Equation; Evaluation; Exposure to; Foundations; Functional Magnetic Resonance Imaging; Future; Generations; Genetic; Goals; Health; Hippocampus (Brain); Human; Image; Instruction; Intervention; Learning; Life; Life Experience; Magnetic Resonance; Measures; Mental Depression; Mental disorders; Methodology; Modality; Modeling; Molecular Probes; Molecular Target; Neurobiology; Neurons; Outcome Measure; Output; Pathology; Pathway interactions; Pattern; Perforant Pathway; Physiology; Predictive Value; Process; Psyche structure; Rat-1; Rattus; Resolution; Rest; Rodent; Series; Signal Transduction; Structure; Synapses; Testing; Thick; Time; Trees; Weight; Work; base; behavior measurement; behavioral outcome; cognitive function; cognitive task; cohort; early experience; early life exposure; emotional behavior; experience; gray matter; infancy; innovation; insight; neocortical; novel; postnatal; potential biomarker; predictive marker; predictive modeling; sensory input; statistics; stem; white matter

In concert with Projects 1-3. this revised Project 4 probes the effects of fragmented early life experience on neuronal network structure and function using magnetic resonance brain imaging (MRI) of rats (with Project 1) and humans (with Projects 2-3). The results will be integrated with parameters generated by the other projects to accomplish the Center's goal of generating predictive models and markers of adolescent mental vulnerabilities. We will start by examining whether fragmented early-life experience influences the structure of brain regions and networks that are salient to cognitive and emotional functions. We then define a trajectory of these structural and functional alterations with development, and their correlation with cognitive and emotional behavior, resulting in potential biomarkers of vulnerability to overt cognitive and emotional pathology. The goal of this project is to employ MRI-derived measures to establish predictors of regional brain connectivity (as well as structural changes) that best correlate with developmental and cognitive vulnerabilities as a function of early life exposure to fragmented maternal signals. This novel analysis will identify a series of pathological changes that occur at varying intervals in the pre-symptomatic period that might guide the timing of future interventions "and provide insights into intrinsic compensatory mechanisms. Its significance derives from the crucial importance of the clinical hypothesis: that fragmented patterns of sensory input modulate the function and connectivity of brain networks. The Project innovation stems from (a) The concept of developmentally evolving neuronal networks as the target of fragmented/unpredictable maternal input, (b) from the use of novel methodologies (e.g.. Structural Equation Modeling); (c) from the use of analysis of distributed hippocampal connectivity using multiple modalities across species, and (d) from inclusion of MRI parameters in multivariate models orchestrated by the Computational Core, to generate potentially predictive models for adolescent vulnerabilities.

与项目1-3一致。这个修订后的项目4探讨了碎片化的早期生活经验对 神经元网络结构和功能使用磁共振脑成像（MRI）的大鼠（与项目 1)人类（项目2-3）。结果将与另一个生成的参数相结合 项目，以实现该中心的目标，产生预测模型和标记的青少年心理 漏洞我们将从研究早期生活经验的碎片化是否会影响结构开始 认知和情感功能的大脑区域和网络。然后我们定义一个 这些结构和功能变化与发展的轨迹，以及它们与认知能力的相关性。 和情绪行为，导致潜在的生物标志物的脆弱性，以公开的认知和情绪 病理 该项目的目标是采用MRI衍生的措施，以建立预测区域大脑 连接（以及结构变化），最好与发展和认知 脆弱性是生命早期暴露于支离破碎的母亲信号的函数。这一新的分析将 确定在症状前期以不同间隔发生的一系列病理变化， 可能指导未来干预的时机“，并提供对内在补偿机制的见解。 它的重要性来自于临床假设的至关重要性： 感觉输入调节大脑网络的功能和连通性。本项目创新源于 (a)神经元网络作为碎片化/不可预测的目标的概念 母体输入，（B）来自使用新方法（例如，结构方程模型）;（c）从使用 使用跨物种的多种模式分析分布式海马连接，以及（d）从 将MRI参数包含在由计算核心编排的多变量模型中，以生成 青少年脆弱性的潜在预测模型。