SP9: Generalizing predictive patterns of treatment (non-) response: from specific phobia and obsessive-compulsive disorder to the anxiety spectrum
SP9: Generalizing predictive patterns of treatment (non-) response: from specific phobia and obsessive-compulsive disorder to the anxiety spectrum
批准号:
468359565
负责人:
Professor Dr. Norbert Kathmann
金额:
$0.0万
依托单位:
依托单位国家:
德国
项目类别:
Research Units
财政年份:
--
资助国家:
德国
项目状态:
未结题
起止时间:
中文摘要
焦虑障碍和强迫症(OCD)是高度共病的,这反映在部分重叠的神经结构和功能上。虽然在目前的分类系统中,强迫症已经从焦虑中移除,但对这些疾病的认知行为治疗(例如,暴露)是非常相似的。因此,包括神经系统层面在内的共性和差异都很难被理解。SP9项目旨在探讨与治疗反应相关的神经结构和功能在多大程度上可以从作为病理性恐惧“模型”障碍的特定恐惧症推广到其他更复杂的焦虑障碍及其相关病症(社交焦虑障碍、恐慌障碍、广场恐怖症、广泛性焦虑障碍和创伤后应激障碍)。其次,通过比较强迫症和焦虑谱之间的特征和预测来检验强迫症单独分类的经验证据。SP9将利用两个回顾性数据集(spidervr研究:n = 174名蜘蛛恐惧症患者;epc研究:n = 116名强迫症患者)来训练预测模型,这些模型将在研究单位的前瞻性队列中重复/交叉验证。所有数据集共享一个共同的神经成像主干,包括神经解剖学数据,静息状态网络(EEG, fMRI)和基于任务的活动和连接,将用于研究泛化梯度。结果将有可能从跨诊断的角度更好地理解NR现象,并有助于指导干预决策。
英文摘要
Anxiety disorders and obsessive-compulsive disorders (OCD) are highly comorbid, which is reflected in partly overlapping neural structure and function. Although OCD was removed from the anxiety section in current classification systems, cognitive-behavioral treatments (e.g., exposure) for these disorders are quite similar. Commonalities, but also differences are hence poorly understood, including a neural systems level. Project SP9 aims to investigate the hypothesis to which extent neural structure and function related to treatment response can be generalized from specific phobia as a “model” disorder for pathological fear to other, more complex anxiety disorders and related conditions (social anxiety disorder, panic disorder, agoraphobia, generalized anxiety disorder and posttraumatic stress disorder). Second, empirical evidence for the separate classification of OCD will be tested by comparing signatures and predictions between OCD and the anxiety spectrum. SP9 will utilize two retrospective datasets (SpiderVR-study: n = 174 spider phobia patients; EPOC-study: n = 116 OCD patients) in order to train predictive models which in turn will be replicated / cross-validated in the prospective cohort from the research unit. All datasets share a common neuroimaging backbone comprising neuroanatomic data, resting-state networks (EEG, fMRI) and task-based activity and connectivity which will be used to investigate generalization gradients. Results will bear potential to better understand the phenomenon of NR from a transdiagnostic perspective and to help guiding intervention decisions.
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财政年份:--
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负责人:Professor Dr. Norbert Kathmann
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依托单位:
海外基金