Acquisition, extinction, and recall of attention biases to threat: Computational modeling and multimodal brain imaging

对威胁的注意偏差的获得、消除和回忆：计算模型和多模态脑成像

基本信息

批准号：
10296986
负责人：
MINGZHOU DING
金额：
$ 45.02万
依托单位：
UNIVERSITY OF FLORIDA
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-08-01 至 2026-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10296986
关键词：
Acceleration Address Amygdaloid structure Animals Anxiety Area Attention Behavior Behavioral Biological Markers Brain Brain imaging Cardiac Clinical Clinical Research Communication Communities Complex Computer Models Computing Methodologies Conditioned Reflex Cues Data Deceleration Diagnostic Diagnostic Procedure Disease Disease susceptibility Electrophysiology (science)Emotions Etiology Event-Related Potentials Extinction (Psychology)Foundations Fright Functional Magnetic Resonance Imaging Goals Heart Rate Human Individual Individual Differences Intervention Laboratories Learning Limbic System Machine Learning Measurement Mental Depression Mental disorders Methods Modeling Monitor Multimodal Imaging National Institute of Mental Health Neurosciences Research Parietal Perception Population Predisposition Process Psychophysics Research Research Domain Criteria Role Safety Sampling Scalp structure Sensory Shapes Signal Transduction Stimulus Stress Structure Study models System Techniques Testing Time Training Translational Research Visual Visual Cortex Visual Perception Visual attention Visual evoked cortical potential Work advanced analytics attentional bias attentional control aversive conditioning base classical conditioning conditioned fear conditioning executive function experience experimental study hemodynamics imaging modality indexing innovation interest learning extinction machine learning algorithm multimodality neuroimaging novel post-traumatic stress potential biomarker predictive modeling relating to nervous system response tool visual neuroscience

Acceleration Address Amygdaloid structure Animals Anxiety Area Attention Behavior Behavioral Biological Markers Brain Brain imaging Cardiac Clinical Clinical Research Communication Communities Complex Computer Models Computing Methodologies Conditioned Reflex Cues Data Deceleration Diagnostic Diagnostic Procedure Disease Disease susceptibility Electrophysiology (science)Emotions Etiology Event-Related Potentials Extinction (Psychology)Foundations Fright Functional Magnetic Resonance Imaging Goals Heart Rate Human Individual Individual Differences Intervention Laboratories Learning Limbic System Machine Learning Measurement Mental Depression Mental disorders Methods Modeling Monitor Multimodal Imaging National Institute of Mental Health Neurosciences Research Parietal Perception Population Predisposition Process Psychophysics Research Research Domain Criteria Role Safety Sampling Scalp structure Sensory Shapes Signal Transduction Stimulus Stress Structure Study models System Techniques Testing Time Training Translational Research Visual Visual Cortex Visual Perception Visual attention Visual evoked cortical potential Work advanced analytics attentional bias attentional control aversive conditioning base classical conditioning conditioned fear conditioning executive function experience experimental study hemodynamics imaging modality indexing innovation interest learning extinction machine learning algorithm multimodality neuroimaging novel post-traumatic stress potential biomarker predictive modeling relating to nervous system response tool visual neuroscience

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项目摘要

Project Summary Classical aversive conditioning is a well-established laboratory model for studying acquisition and extinction of defensive responses. In experimental animals, as well as in humans, research to date has been mainly focused on the role of limbic structures (e.g., the amygdala) in these responses. Recent evidence has begun to stress the important contribution by the brain’s sensory and attention control systems in maintaining the neural representations of conditioned responses and in facilitating their extinction. The proposed research breaks new ground by combining novel neuroimaging techniques with advanced computational methods to examine the brain’s visual and attention processes underlying fear acquisition and extinction in humans. Major advances will be made along three specific aims. In Aim 1, we characterize the brain network dynamics of visuocortical threat bias formation, extinction, and recall in a two-day learning paradigm. In Aim 2, we establish and test a computational model of threat bias generalization. In Aim 3, we examine the relation between individual differences in generalization and recall of conditioned visuocortical threat biases and individual differences in heightened autonomic reactivity to conditioned threat, a potential biomarker for assessing the predisposition to developing the disorders of fear and anxiety. It is expected that accomplishing these research aims will address two NIMH strategic priorities: defining the circuitry and brain networks underlying complex behaviors (Objective 1) and identifying and validating new targets for treatment that are derived from the understanding of disease mechanisms (Objective 3). It is further expected that this project will enable a paradigm shift in research on dysfunctional attention to threat from one that focuses primarily on limbic-prefrontal circuits to one that emphasizes the interactions among sensory, attention, executive control and limbic systems.

项目摘要经典的厌恶调节是一个完善的实验室模型，用于研究采集和扩展防御性反应。在实验动物以及人类中，迄今为止的研究主要集中在关于边缘结构（例如杏仁核）在这些反应中的作用。最近的证据已经开始强调大脑的感觉和注意力控制系统在保持中性方面的重要贡献条件响应的表示并支持其扩展。拟议的研究破坏了新的通过将新颖的神经影像技术与先进的计算方法相结合来检查地面大脑的视觉和关注过程是人类恐惧获取和扩展的基础。主要进步将以三个特定的目标进行。在AIM 1中，我们表征了视觉皮层的大脑网络动力学在为期两天的学习范式中，威胁偏见的形成，扩展和召回。在AIM 2中，我们建立并测试威胁偏见概括的计算模型。在AIM 3中，我们检查了个人之间的关系有条件的视觉皮质威胁偏见和个体差异的概括和回忆的差异对条件威胁的自主反应提高了，这是评估易感性的潜在生物标志物发展恐惧和动画的疾病。预计完成这些研究目标将解决两个NIMH战略重点：定义复杂行为的基础电路和大脑网络（客观） 1）并识别并验证并验证从对疾病的理解中得出的治疗的新目标机制（目标3）。进一步预期，该项目将使研究范式转变对威胁的关注功能失调，该威胁主要集中于边缘围绕一个圆圈的威胁强调感官，注意力，执行控制和边缘系统之间的相互作用。