BACKGROUND: Reduced reward learning might contribute to the onset and maintenance of major depressive disorder (MDD). In particular, the inability to utilize rewards to guide behavior is hypothesized to be associated with anhedonia, a core feature and potential trait marker of MDD. Few studies have investigated whether reduced reward learning normalizes with treatment and/or reward learning predicts clinical outcome. Our goal was to test whether MDD is characterized by reduced reward learning, especially in the presence of anhedonic symptoms, and to investigate the relationship between reward learning and MDD diagnosis after 8 weeks of treatment. METHODS: Seventy-nine inpatients and 63 healthy control subjects performed a probabilistic reward task yielding an objective measure of participants' ability to modulate behavior as a function of reward. We compared reward responsiveness between depressed patients and control subjects, as well as high- versus low-anhedonic MDD patients. We also evaluated whether reward-learning deficits predicted persistence of MDD after 8 weeks of treatment. RESULTS: Relative to control subjects, MDD patients showed reduced reward learning. Moreover, patients with high anhedonia showed diminished reward learning compared with patients with low anhedonia. Reduced reward learning at study entry increased the odds of a persisting diagnosis of MDD after 8 weeks of treatment (odds ratio 7.84). CONCLUSIONS: Our findings indicate that depressed patients, especially those with anhedonic features, are characterized by an impaired ability to modulate behavior as a function of reward. Moreover, reduced reward learning increased the odds for the diagnosis of MDD to persist after 8 weeks of treatment.
BACKGROUND: Reduced reward learning might contribute to the onset and maintenance of major depressive disorder (MDD). In particular, the inability to utilize rewards to guide behavior is hypothesized to be associated with anhedonia, a core feature and potential trait marker of MDD. Few studies have investigated whether reduced reward learning normalizes with treatment and/or reward learning predicts clinical outcome. Our goal was to test whether MDD is characterized by reduced reward learning, especially in the presence of anhedonic symptoms, and to investigate the relationship between reward learning and MDD diagnosis after 8 weeks of treatment. METHODS: Seventy-nine inpatients and 63 healthy control subjects performed a probabilistic reward task yielding an objective measure of participants' ability to modulate behavior as a function of reward. We compared reward responsiveness between depressedpatients and control subjects, as well as high- versus low-anhedonic MDDpatients. We also evaluated whether reward-learning deficits predicted persistence of MDD after 8 weeks of treatment. RESULTS: Relative to control subjects, MDDpatients showed reduced reward learning. Moreover, patients with high anhedonia showed diminished reward learning compared with patients with low anhedonia. Reduced reward learning at study entry increased the odds of a persisting diagnosis of MDD after 8 weeks of treatment (odds ratio 7.84). CONCLUSIONS: Our findings indicate that depressedpatients, especially those with anhedonic features, are characterized by an impaired ability to modulate behavior as a function of reward. Moreover, reduced reward learning increased the odds for the diagnosis of MDD to persist after 8 weeks of treatment.
Authors: Kathryn D Boger; Randy P Auerbach; Pia Pechtel; Alisa B Busch; Shelly F Greenfield; Diego A Pizzagalli Journal: J Psychother Integr Date: 2014-06
Authors: Mary L Phillips; Henry W Chase; Yvette I Sheline; Amit Etkin; Jorge R C Almeida; Thilo Deckersbach; Madhukar H Trivedi Journal: Am J Psychiatry Date: 2015-02-01 Impact factor: 18.112
Authors: Chloe C Boyle; Kate R Kuhlman; Larissa N Dooley; Marcie D Haydon; Theodore F Robles; Yuen-Siang Ang; Diego A Pizzagalli; Julienne E Bower Journal: Psychoneuroendocrinology Date: 2018-11-20 Impact factor: 4.905
Authors: Michael T Treadway; Roee Admon; Amanda R Arulpragasam; Malavika Mehta; Samuel Douglas; Gordana Vitaliano; David P Olson; Jessica A Cooper; Diego A Pizzagalli Journal: Biol Psychiatry Date: 2017-03-28 Impact factor: 13.382
Authors: Kaitlin E DeWilde; Cara F Levitch; James W Murrough; Sanjay J Mathew; Dan V Iosifescu Journal: Ann N Y Acad Sci Date: 2015-02-03 Impact factor: 5.691