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， 这给美国带来了无法估量的人类痛苦沿着而来的是每年6000亿美元的经济负担。的 负面情绪的大脑基础一直是耗资巨大的研究工作的重点，但两个关键障碍已经减缓 科学发现首先，没有一种机制可以解释负面情绪是如何在大脑中产生的。一 这个障碍的解决方案可以在预测处理中找到，这是一种新兴的统一大脑的范例 跨情绪、认知、知觉、运动和其他心理领域的机制。预测 加工解释说，大脑不断地构造预测信号来控制内脏， 运动，而这些预测信号的副本预测来自身体的传入感觉信号 和外部世界。传入的感觉信号被认为是作为预测在整个大脑中传递 错误信号到目前为止，还没有研究考察与信号流动力学相关的负面影响。 大脑的特殊结构特征为了克服这一障碍，我将利用一个概念性的 我们实验室的创新和三十年来在哺乳动物中进行的追踪研究，以检验预测 信号和预测误差信号可以在大脑皮层和皮层下的特定层上被追踪 结构.简而言之，预测信号被认为起源于皮层的深层， 开发（例如，前中扣带皮层，aMCC，这是重要的内脏控制和影响） 并到达皮层下结构（例如，下丘脑，参与内脏控制）和初级感觉 皮质（例如，初级视觉皮层（V1）。内感受性预测误差信号应起源于皮层下 结构（例如，下丘脑）和其他（外感受性）感觉预测错误应该起源于原发性 感觉皮层（例如，V1），分别到达皮层的上层和深层， 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： 神经成像方法缺乏足够的空间分辨率来测量深部皮层与上部皮层的活动 层和小的皮层下结构。新开发的超高场（7特斯拉）功能磁共振成像技术， 有足够的决心克服这一障碍。通过这一方法论创新，我将探讨 通过7T fMRI数据集的功能连接分析， 我们实验室策划的92名健康受试者被要求预测视觉或躯体感觉刺激 （预测期），要么是不愉快的或中性的，然后与刺激（预测 误差周期）。在两个具体目标中，我将1）测量负面影响期间的动态预测信号，以及2） 表征负面影响期间的预测误差信号。这项拟议中的研究有望提供一种新的 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 消极情绪是许多精神疾病的标志性特征。

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.