Abstract
Despite the prominence of anhedonic symptoms associated with diverse neuropsychiatric conditions, there are currently no approved therapeutics designed to attenuate the loss of responsivity to previously rewarding stimuli. However, the search for improved treatment options for anhedonia has been reinvigorated by a recent reconceptualization of the very construct of anhedonia, including within the Research Domain Criteria (RDoC) initiative. This chapter will focus on the RDoC Positive Valence Systems construct of reward learning generally and sub-construct of probabilistic reinforcement learning specifically. The general framework emphasizes objective measurement of a subject’s responsivity to reward via reinforcement learning under asymmetrical probabilistic contingencies as a means to quantify reward learning. Indeed, blunted reward responsiveness and reward learning are central features of anhedonia and have been repeatedly described in major depression. Moreover, these probabilistic reinforcement techniques can also reveal neurobiological mechanisms to aid development of innovative treatment approaches. In this chapter, we describe how investigating reward learning can improve our understanding of anhedonia via the four RDoC-recommended tasks that have been used to probe sensitivity to probabilistic reinforcement contingencies and how such task performance is disrupted in various neuropsychiatric conditions. We also illustrate how reverse translational approaches of probabilistic reinforcement assays in laboratory animals can inform understanding of pharmacological and physiological mechanisms. Next, we briefly summarize the neurobiology of probabilistic reinforcement learning, with a focus on the prefrontal cortex, anterior cingulate cortex, striatum, and amygdala. Finally, we discuss treatment implications and future directions in this burgeoning area.
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Acknowledgments
BDK was partially supported by grant R01 DA047575 from the National Institute on Drug Abuse. AD was partially supported by grants R01 MH121352 and UH3 MH109334 from the National Institute of Mental Health and R01 AA026560 from the National Institute on Alcohol Abuse and Alcoholism. DAP was partially supported by grants R01 MH095809, P50 MH119467, R01 MH108602, R37 MH068376, and UH3 MH109334 from the National Institute of Mental Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Health.
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Over the past 3 years, Dr. Pizzagalli has received consulting fees from Albright Stonebridge Group, Boehringer Ingelheim, Compass Pathways, Concert Pharmaceuticals, Engrail Therapeutics, Neumora Therapeutics (former BlackThorn Therapeutics), Neurocrine Biosciences, Neuroscience Software, Otsuka Pharmaceuticals, and Takeda Pharmaceuticals; honoraria from the Psychonomic Society (for editorial work), one honorarium from Alkermes, and research funding from National Institute of Mental Health, Dana Foundation, Brain and Behavior Research Foundation, Millennium Pharmaceuticals. In addition, he has received stock options from BlackThorn Therapeutics, Compass Pathways and Neuroscience Software. Dr. Pizzagalli has a financial interest in Neumora Therapeutics (former BlackThorn Therapeutics), which has licensed the copyright to the Probabilistic Reward Task through Harvard University. Dr. Pizzagalli’s interests were reviewed and are managed by McLean Hospital and Massachusetts General Brigham in accordance with their conflict-of-interest policies. Dr. Der-Avakian holds equity ownership in PAASP US. No funding from these entities was used to support the current work, and all views expressed are solely those of the authors. Dr. Kangas reports no financial relationships with commercial interest.
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Kangas, B.D., Der-Avakian, A., Pizzagalli, D.A. (2022). Probabilistic Reinforcement Learning and Anhedonia. In: Pizzagalli, D.A. (eds) Anhedonia: Preclinical, Translational, and Clinical Integration. Current Topics in Behavioral Neurosciences, vol 58. Springer, Cham. https://doi.org/10.1007/7854_2022_349
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