Probing negative affect circuits in humans using 7T fMRI

使用 7T fMRI 探测人类的负面影响回路

• 批准号: 10752127
• 负责人: Philip Deming
• 金额: $ 7.4万
• 依托单位: NORTHEASTERN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10752127
• 关键词: Affect; Anatomy; Anterior; Anxiety; Architecture; Area; Bipolar Disorder; Brain; Cerebral cortex; Cognition; Collaborations; Computer Models; Country; Data; Data Set; Development; Diagnostic; Disease; Economic Burden; Emotions; Engineering; Functional Magnetic Resonance Imaging; Goals; Human; Hypothalamic structure; Image; Learning; Mammals; Measures; Mental Depression; Mental disorders; Methodology; Methods; Mood Disorders; Moods; Motor; Movement; Negative Valence; Participant; Pattern; Perception; Positioning Attribute; Public Health; Research; Research Domain Criteria; Resolution; Sampling; Schizophrenia; Schools; Scientist; Sensory; Signal Transduction; Stimulus; Structural Models; Structure; Techniques; Testing; Training; Visual; affective neuroscience; area striata; career; cost; experience; human subject; innovation; negative affect; negative mood; neural circuit; neuroimaging; next generation; novel; post-doctoral training; prevent; psychologic; sensory cortex; skills; somatosensory; theories

Project Summary Negative mood is a common feature of anxiety, depression, bipolar disorder, and schizophrenia, which inflict immeasurable human suffering along with a combined economic burden of $600 billion in the US each year. The brain basis of negative affect has been the focus of costly research efforts, but two critical barriers have slowed scientific discovery. First, there is no mechanistic explanation for how negative affect is caused in the brain. A solution to this barrier can be found in predictive processing, an emerging paradigm for unifying brain mechanisms across emotion, cognition, perception, movement, and other psychological domains. Predictive processing accounts posit that the brain continuously constructs prediction signals to control visceromotor and motor movements, while copies of these prediction signals anticipate incoming sensory signals from the body and the external world. Incoming sensory signals are thought to be relayed throughout the brain as prediction error signals. No study to date has examined negative affect in relation to the dynamics of signal flow within the specific architectural features of the brain. To surmount this barrier, I will take advantage of a conceptual innovation from our lab and thirty years of tract-tracing studies in mammals to test the hypothesis that prediction signals and prediction error signals can be traced across specific layers of cerebral cortex and subcortical structures. Briefly, prediction signals are thought to originate in deep layers of cortices that have less laminar development (e.g., anterior midcingulate cortex, aMCC, which is important for visceromotor control and affect) and arrive to subcortical structures (e.g., hypothalamus, involved in visceromotor control) and primary sensory cortices (e.g., primary visual cortex, V1). Interoceptive prediction error signals should originate from subcortical structures (e.g., hypothalamus) and other (exteroceptive) sensory prediction errors should originate in primary sensory cortices (e.g., V1), arriving to the upper and deep layers, respectively, of cortices with less laminar development (e.g., aMCC). In human subjects, these hypotheses remain to be tested due to a second barrier: neuroimaging methods have lacked sufficient spatial resolution to measure activity in deep vs. upper cortical layers and small subcortical structures. Newly developed ultra-high field (7 Tesla) fMRI techniques have sufficient resolution to overcome this barrier. With this methodological innovation, I will probe the mechanisms that cause negative affect in the circuitry outlined above via functional connectivity analyses of a 7T fMRI dataset our lab has curated. Ninety-two healthy subjects were instructed to anticipate visual or somatosensory stimuli (prediction period) that were either unpleasant or neutral and then were presented with the stimuli (prediction error period). In two specific aims, I will 1) measure dynamic prediction signals during negative affect, and 2) characterize prediction error signals during negative affect. The proposed research promises to deliver a new paradigm for studying the brain basis of negative affect, with the ultimate goal of developing targeted treatments for negative mood, a hallmark feature of many mental illnesses.

项目摘要 负面情绪是焦虑，抑郁，躁郁症和精神分裂症的常见特征，这会导致 每年美国，不可估量的人类苦难以及美国6000亿美元的综合经济负担。这 负面影响的大脑基础一直是昂贵的研究工作的重点，但是两个关键障碍却放慢了 科学发现。首先，对于大脑中的负面影响是如何引起的。一个 可以在预测处理中找到解决此障碍的方法，这是统一大脑的新兴范式 情绪，认知，感知，运动和其他心理领域的机制。预测性 处理帐户认为大脑连续构建预测信号以控制内脏运动和 电动机运动，而这些预测信号的副本则可以预期从体内传入的感觉信号 和外部世界。传入的感觉信号被认为是整个大脑中传递的预测 错误信号。迄今为止，尚无研究检查与信号流动动力学有关的负面影响 大脑的特定建筑特征。为了克服这个障碍，我将利用一个概念 我们实验室的创新以及三十年的哺乳动物研究研究，以检验预测的假设 信号和预测误差信号可以在大脑皮层和皮层的特定层中追溯到 结构。简而言之，预测信号被认为起源于层状较少的皮质的深层 开发（例如，前中期皮层，AMCC，这对于内脏控制和影响很重要） 并到达皮层结构（例如下丘脑，参与内脏运动控制）和主要感觉 皮质（例如，主要视觉皮层，V1）。感知性预测错误信号应起源于皮层下 结构（例如下丘脑）和其他（外部感受）的感觉预测错误应起源于主要 感觉皮质（例如V1）分别到达层状较少的皮质的上层和深层 开发（例如，AMCC）。在人类受试者中，由于第二个障碍，这些假设仍有待检验： 神经影像学方法缺乏足够的空间分辨率来测量深层皮质的活性 层和小皮层结构。新开发的超高场（7特斯拉）fMRI技术具有 足够的解决方案来克服这一障碍。通过这种方法上的创新，我将探究机制 通过7T fMRI数据集的功能连接分析，这会导致上述电路的负面影响 我们的实验室策划了。指示92名健康受试者预测视觉或体感刺激 （预测期）不愉快或中性，然后用刺激表示（预测 错误期）。在两个具体目标中，我将1）测量负面影响期间动态预测信号，以及2） 在负面影响期间表征预测误差信号。拟议的研究有望提供新的 用于研究负面影响的大脑基础的范式，其最终目标是开发目标治疗 对于负面情绪，这是许多精神疾病的标志性特征。