Volume 37 Issue 4
Jul.  2016
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Ming LI, Shinn-Yi CHOU. Modeling postpartum depression in rats: theoretic and methodological issues. Zoological Research, 2016, 37(4): 229-236. doi: 10.13918/j.issn.2095-8137.2016.4.229
Citation: Ming LI, Shinn-Yi CHOU. Modeling postpartum depression in rats: theoretic and methodological issues. Zoological Research, 2016, 37(4): 229-236. doi: 10.13918/j.issn.2095-8137.2016.4.229

Modeling postpartum depression in rats: theoretic and methodological issues

doi: 10.13918/j.issn.2095-8137.2016.4.229
Funds:  The preparation of this review was partially supported by a grant from the National Institute of Mental Health (5R01MH097718-02), U.S.A.
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  • Corresponding author: Ming LI
  • Received Date: 2015-11-10
  • Rev Recd Date: 2016-01-20
  • Publish Date: 2016-07-18
  • The postpartum period is when a host of changes occur at molecular, cellular, physiological and behavioral levels to prepare female humans for the challenge of maternity. Alteration or prevention of these normal adaptions is thought to contribute to disruptions of emotion regulation, motivation and cognitive abilities that underlie postpartum mental disorders, such as postpartum depression. Despite the high incidence of this disorder, and the detrimental consequences for both mother and child, its etiology and related neurobiological mechanisms remain poorly understood, partially due to the lack of appropriate animal models. In recent decades, there have been a number of attempts to model postpartum depression disorder in rats. In the present review, we first describe clinical symptoms of postpartum depression and discuss known risk factors, including both genetic and environmental factors. Thereafter, we discuss various rat models that have been developed to capture various aspects of this disorder and knowledge gained from such attempts. In doing so, we focus on the theories behind each attempt and the methods used to achieve their goals. Finally, we point out several understudied areas in this field and make suggestions for future directions.
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