Animal models of recurrent or bipolar depression. (3rd May 2016)

• Record Type: Journal Article
• Authors: Kato, T.; Kasahara, T.; Kubota-Sakashita, M.; Kato, T.M.; Nakajima, K.
• Is Part Of: Neuroscience. Volume 321(2016)
• Page Start: 189
• Page End: 196
• Publication Date: 2016-05-03
• Subjects: ADHD attention deficit/hyperactivity disorder -- DICE-K doxycycline-inhibited circuit-exocytosis knockdown -- DREADD designer receptors exclusively activated by designer drugs -- DRN dorsal raphe nucleus -- mPFC medial prefrontal cortex -- OB olfactory bulbectomized -- RDoC Research Domain Criteria -- VTA ventral tegmental area; depressive disorder -- bipolar disorder -- model mice; Neurochemistry -- Periodicals; Neurophysiology -- Periodicals; Neurology -- Periodicals; Neurochimie -- Périodiques; Neurophysiologie -- Périodiques; Neurochemistry; Neurophysiology; Electronic journals; Periodicals; Electronic journals; 612.8
• DOI: 10.1016/j.neuroscience.2015.08.016
• Languages: English
• ISSNs: 0306-4522

Abstract

Highlights: Animal models showing recurrent mood episodes are necessary. Animal models of mental disorders should satisfy three validity criteria. Human diagnostic criteria could be used for the assessment of animal models. Several animal models somehow model recurrent mood episodes. Abstract: Animal models of mental disorders should ideally have construct, face, and predictive validity, but current animal models do not always satisfy these validity criteria. Additionally, animal models of depression rely mainly on stress-induced behavioral changes. These stress-induced models have limited validity, because stress is not a risk factor specific to depression, and the models do not recapitulate the recurrent and spontaneous nature of depressive episodes. Although animal models exhibiting recurrent depressive episodes or bipolar depression have not yet been established, several researchers are trying to generate such animals by modeling clinical risk factors as well as by manipulating a specific neural circuit using emerging techniques.