混淆
萧条(经济学)
抑郁症动物模型
机制(生物学)
脆弱性(计算)
心理学
心理弹性
医学
神经科学
重性抑郁障碍
临床心理学
精神科
抗抑郁药
认知
焦虑
心理治疗师
计算机科学
病理
哲学
经济
宏观经济学
认识论
计算机安全
作者
Qingzhong Wang,Matthew A. Timberlake,Kevin Prall,Yogesh Dwivedi
标识
DOI:10.1016/j.pnpbp.2017.04.008
摘要
Major depression disorder (MDD) is a debilitating mental illness with significant morbidity and mortality. Despite the growing number of studies that have emerged, the precise underlying mechanisms of MDD remain unknown. When studying MDD, tissue samples like peripheral blood or post-mortem brain samples are used to elucidate underlying mechanisms. Unfortunately, there are many uncontrollable factors with such samples such as medication history, age, time after death before post-mortem tissue was collected, age, sex, race, and living conditions. Although these factors are critical, they introduce confounding variables that can influence the outcome profoundly. In this regard, animal models provide a crucial approach to examine neural circuitry and molecular and cellular pathways in a controlled environment. Further, manipulations with pharmacological agents and gene editing are accepted methods of studying depression in animal models, which is impossible to employ in human patient studies. Here, we have reviewed the most widely used animal models of depression and delineated the salient features of each model in terms of behavioral and neurobiological outcomes. We have also illustrated the current challenges in using these models and have suggested strategies to delineate the underlying mechanism associated with vulnerability or resilience to developing depression.
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