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Trait "pessimism" is associated with increased sensitivity to negative feedback in rats
1Affective Cognitive Neuroscience Laboratory, Department of Behavioral Neuroscience and Drug Development, Institute of Pharmacology, Polish Academy of Sciences, 12 Smetna Street, 31-343, Krakow, Poland. rygula@gmail.com.
Cognitive, Affective & Behavioral Neuroscience
|February 24, 2016
Summary
Pessimistic rats show heightened sensitivity to negative feedback, indicating a link between cognitive biases and depression vulnerability. This study explores judgment biases in animal models of depression.
Area of Science:
- Neuroscience
- Cognitive Psychology
- Animal Models
Background:
- Cognitive theories link judgment bias to depression vulnerability.
- Previous research showed pessimistic bias correlates with stress-induced anhedonia and reduced motivation in rats.
Purpose of the Study:
- To investigate the impact of trait pessimism on cognitive processes related to depression.
- To compare the sensitivity of optimistic and pessimistic rats to positive and negative feedback.
Main Methods:
- Rats were trained on a probabilistic reversal-learning (PRL) task to assess feedback sensitivity.
- Ambiguous-cue interpretation (ACI) tests classified rats into optimistic and pessimistic groups.
- Behavioral responses to feedback were analyzed.
Main Results:
- Pessimistic rats exhibited significantly higher sensitivity to negative feedback compared to optimistic rats.
- This heightened sensitivity was evidenced by an increased proportion of lose-shift behaviors in pessimistic rats.
- The findings suggest an interrelation between cognitive biases and vulnerability to depressive disorders.
Conclusions:
- Cognitive biases, specifically judgment bias, are associated with vulnerability to depression.
- Pessimistic traits in rats are linked to increased sensitivity to negative feedback.
- These findings support the co-existence of cognitive biases that may predict depressive disorder vulnerability.
Keywords:
Ambiguous-cue interpretationCognitive judgment biasFeedback sensitivityOptimismPessimismProbabilistic reversal learningRat
