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CRNS: Model of hippocampal-amygdala interaction: Implications for PTSD

CRNS：海马-杏仁核相互作用模型：对 PTSD 的影响

基本信息

批准号：
8308540
负责人：
CATHERINE E MYERS
金额：
$ 17.77万
依托单位：
VETERANS BIOMEDICAL RESEARCH INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-08-01 至 2014-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8308540
关键词：
Accounting Address Adult Affect Alcohol abuse Alcohol consumption Alcohol dependence Alcoholism Amygdaloid structure Animal Model Anxiety Anxiety Disorders Area Behavior Behavioral Bilateral Brain Brain Injuries Cell Nucleus Chemicals Cognitive Collaborations Comorbidity Complex Computer Simulation Data Dependency Development Diagnostic Disease Event Extinction (Psychology)Family Fright Functional disorder Funding Future Galvanic Skin Response Heart Rate Hippocampus (Brain)Human Hyperactive behavior Impairment Individual Instruction Lead Learning Lesion Metabolic Modeling Outcomes Research Pathology Patients Post-Traumatic Stress Disorders Prefrontal Cortex Prevention Prevention strategy Principal Investigator Process Risk Factors Role Series Shock Simulate Stimulus Stress Structure Substance abuse problem Symptoms Testing Time United States National Institutes of Health Veterans Work brain behavior computational neuroscience conditioned fear conditioning disorder subtype prevent response tool

项目摘要

In response to NSF/NIH CRCNS (NS-08-008), we propose a new collaborative project to develop a computational model of the interaction of hippocampus, amygdala, and ventromedial prefrontal cortex in conditioning, extinction, and contextual processing. The model will be applied to data collected from patients with post-traumatic stress disorder (PTSD), which is associated with volumetric and metabolic alterations in these areas. The computational model will also allow us to investigate the possibility that there may be different subtypes of PTSD that involve different nodes of brain dysfunction contributing to a common symptomatology. In addition to PTSD, the computational work may also have future applications to modeling other anxiety disorders and substance abuse disorders (including alcohol abuse and alcoholism) that share many of the same brain substrates as, and that are often co-morbid with, PTSD. ' In parallel with the computational modeling, empirical studies of contextual processing will be conducted in healthy adults and in patients with PTSD, to generate further data to constrain the model, while the model itself will generate new predictions that may drive further empirical studies. The proposed work will increase our understanding of PTSD and examine the idea that it may not be a unified disorder, but a family of pathologies that share features with each other and also with the broader spectrum of anxiety disorders. There will be implications for prevention, through better understanding of pre-existing risk factors, and for optimizing treatment that targets possible PTSD subtypes. Although the empirical work will focus on PTSD, this disorder and alcohol abuse show very high comorbidity, suggesting shared vulnerability. PTSD patients may also use alcohol to "self-medicate" hyperarousal symptoms. Understanding the interaction between PTSD and alcohol abuse may lead to better treatments for comorbid patients as well as development of prevention strategies targeted to individuals with pre-existing vulnerabilities for developing anxiety disorders vs. chemical dependency vs. both. The project represents a new collaboration among experts on computational neuroscience ofthe hippocampus in conditioning and contextual processing (Myers), on the structural, functional, and behavioral abnormalities in PTSD (Gilbertson, Orr), and on classical fear conditioning in humans and animal models of anxiety (Servatius). RELEVANCE (See instructions): The proposed work will increase our understanding of PTSD, with implications for prevention, through better understanding of pre-existing risk factors, and for optimizing treatment to possible PTSD subtypes. In addition, the computational model of hippocampal-amygdala interaction may have applications to other disorders, particularly alcohol abuse, that share many ofthe same brain substrates, and that may have common pre-existing vulnerabilities; the computational model will provide a framework that can be used to explore these ideas, and may suggest ways to optimize treatment for comorbid patients.

为了响应NSF/NIH CRCNS (NS-08-008)，我们提出了一个新的合作项目来开发一种新的

项目成果

期刊论文数量（21）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Enhanced avoidance learning in behaviorally inhibited young men and women.

DOI：
10.3109/10253890.2012.744391
发表时间：
2013-05
期刊：
Stress (Amsterdam, Netherlands)
影响因子：
0
作者：
Sheynin J;Shikari S;Gluck MA;Moustafa AA;Servatius RJ;Myers CE
通讯作者：
Myers CE

Probabilistic reward- and punishment-based learning in opioid addiction: Experimental and computational data.

DOI：
10.1016/j.bbr.2015.09.018
发表时间：
2016-01-01
期刊：
Behavioural brain research
影响因子：
2.7
作者：
Myers CE;Sheynin J;Balsdon T;Luzardo A;Beck KD;Hogarth L;Haber P;Moustafa AA
通讯作者：
Moustafa AA

Acquired equivalence in U.S. veterans with symptoms of posttraumatic stress: reexperiencing symptoms are associated with greater generalization.

DOI：
10.1002/jts.21974
发表时间：
2014-12
期刊：
JOURNAL OF TRAUMATIC STRESS
影响因子：
3.3
作者：
Kostek, John A.;Beck, Kevin D.;Gilbertson, Mark W.;Orr, Scott P.;Pang, Kevin C. H.;Servatius, Richard J.;Myers, Catherine E.
通讯作者：
Myers, Catherine E.

The personality trait of behavioral inhibition modulates perceptions of moral character and performance during the trust game: behavioral results and computational modeling.

行为抑制的人格特征在信任游戏中调节道德品质和表现的感知：行为结果和计算模型。