Abstract

The Flinders Sensitive Line (FSL) rat, selectively bred for increased responses to the anticholinesterase DFP, was originally proposed as an animal model of depression because, like depressed humans, it is supersensitive to the behavioral and hormonal effects of cholinergic (muscarinic) agonists. The present review critically examines earlier and recent data collected on FSL rats to assess whether the model has good face, construct and/or predictive validity. With respect to face validity, FSL rats resemble depressed humans, at least superficially, in that they demonstrate: (a) reduced locomotor activity, (b) reduced body weight, (c) increased REM sleep, and (d) cognitive (learning) difficulties. So far, studies designed to assess the presence of anhedonia, a cardinal symptom of melancholic depression, have been inconclusive, but there are trends for the FSL rats to be more anhedonic than their control counterparts, the Flinders Resistant Line (FRL) rats, when exposed to chronic mild stress. Thus, FSL rats fulfill the criterion of face validity. Because FSL rats also are more sensitive to cholinergic agonists and have phase advanced circadian rhythms, they meet the criteria for the cholinergic and circadian rhythm models of depression and, therefore, have good construct validity. A key behavioral symptom exhibited by the FSL rat is demonstration of an exaggerated immobility when exposed to stressors such as foot shock and forced swimming. This behavioral abnormality has been normalized by a number of well-recognized antidepressant drugs such as imipramine and desipramine, as well as newer generation antidepressants with promising clinical effects such as sertraline and rolipram. However, several treatments that have not been routinely used to treat depression (lithium, exposure to bright light, the anticholinesterase DFP) have been ineffective in reversing the exaggerated immobility. Thus, the evidence in the present review indicates that the FSL rat model of depression fulfills the criteria of face, construct, and predictive validities.

Full Text
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