Probing negative affect circuits in humans using 7T fMRI

项目摘要 消极情绪是焦虑、抑郁、双相情感障碍和精神分裂症的共同特征，这些疾病会造成 不可估量的人类痛苦以及美国每年6000亿美元的经济负担。这个 负面情绪的大脑基础一直是耗资巨大的研究努力的重点，但有两个关键障碍已经放缓 科学发现。首先，对于负面情绪是如何在大脑中产生的，没有机械论的解释。一个 这一障碍的解决方案可以在预测处理中找到，这是一种新兴的大脑统一范式 跨越情绪、认知、感知、运动和其他心理领域的机制。预测性 处理账户假设大脑不断构建预测信号来控制内脏运动和 运动动作，而这些预测信号的副本预测从身体传入的感觉信号 以及外部世界。传入的感觉信号被认为是通过大脑传递的预测 错误信号。到目前为止，还没有研究过与信号流动的动力学有关的负面影响 大脑的特定结构特征。为了跨越这个障碍，我将利用一个概念性的 我们实验室的创新和30年来对哺乳动物的轨迹追踪研究，以验证预测 信号和预测误差信号可以跨大脑皮层和皮质下的特定层进行追踪 结构。简而言之，预测信号被认为起源于具有较少层流的皮质深层。 发育(例如，前中扣带皮质，aMCC，这对内脏运动控制和影响很重要) 并到达皮质下结构(例如，参与内脏运动控制的下丘脑)和初级感觉 大脑皮层(如初级视觉皮质，V1)。感觉间预测误差信号应起源于皮层下 结构(如下丘脑)和其他(外感)感官预测错误应起源于初级 感觉皮层(例如，V1)，分别到达具有较少层数的皮质的上层和深层 发展(例如，aMCC)。在人类受试者中，由于第二个障碍，这些假设仍然有待检验： 神经成像方法缺乏足够的空间分辨率来测量深皮质与上皮质的活动。 各层和皮质下的小结构。新开发的超高场(7特斯拉)功能磁共振技术 有足够的决心克服这一障碍。通过这一方法创新，我将探索其机制。 通过对7T fMRI数据集的功能连通性分析，在上面概述的电路中引起负面影响 我们的实验室已经策划了。92名健康受试者被要求预测视觉或体感刺激 (预测期)令人不快或中性的，然后呈现刺激(预测 错误周期)。在两个具体目标中，我将1)测量负面情绪期间的动态预测信号，2) 描述负面影响期间的预测误差信号。这项拟议的研究承诺提供一种新的 研究负面情绪的大脑基础的范例，最终目标是开发有针对性的治疗方法 对于负面情绪，这是许多精神疾病的标志特征。

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.