A pioneering study recently revealed that dopamine levels increase as a reaction to stressful stimuli, not only pleasurable ones, potentially rewriting details about a critical mediator of many mental disorders known as the "feel-good" hormone.
According to a Medical Xpress report, this discovery has caused the rethinking of treatment for both psychiatric disease and addiction.
The study was led by Cody Siciliano and Erin Calipari, both pharmacology assistant professors and postdoctoral fellow Munir Gunes Kutlu in the laboratory of Calipari.
According to Calipari, in the press, dopamine is frequently referred to as a "pleasure molecule" or a "reward molecule."
The postdoctoral fellow, also a member of the faculty at the Vanderbilt Brain Institute and the Center for Addiction Research, added, "in the scientific community," the study has helped in the understanding of the role of dopamine in learning, and memory is more multifaceted than that, although there has not been a complete and precise theory that could explain what dopamine is exactly doing the brain.
The 'Reward Prediction Error Theory'
The predominant model, also known as the reward prediction error theory, is based on the notion that dopamine signals forecast when rewards will occur.
Such a theory proposes that dopamine is a tracker of each error made when rewards are attempted to be achieved. The researchers presented that RPE is only precise in a subject of learning circumstances by proving that, as rewards are increasing dopamine, "so do stressful stimuli," explained Calipari.
The assistant professor also said they then explained that dopamine is not a reward molecule at all. Instead, it helps encode information about all sorts of essential and relevant occurrences and drive adaptive behavior, regardless of if it is favorable or not.
The study authors collaborated with the professor and vice-chair of biochemistry and molecular medicine at UC Davis Lin Tian to employ cutting-edge technology to investigate an unparalleled diversity of neurobehavioral processes related to dopamine release.
Machine Learning and Computational Modeling Used
The researchers employed machine learning and computational modeling to assess the data, along with "optogenetic manipulations," which utilizes light to regulate the activity of genetically altered neurons.
Such an analysis established a groundbreaking computational model of behavior, showing precise prediction of the behavioral effect of optogenetic alarms of dopamine release.
Referring to their finding, Calipari concluded that the research replaces the present insight with a formalized theory and calls for revision of the so-called "textbook facts" about dopamine in the central nervous system.
A mutual theme of all drugs of abuse is that they increase dopamine release in the brain, which helped feed the idea of dopamine as a reward molecule.
According to Vanderbilt Center for Addiction Research director Danny Winder, this study, published in Current Biology, clearly validates a much more sophisticated function for such a neurotransmitter, and it means there is a need to rethink models of addition depending on the dopamine or drug reward mentality.
Rewriting Facts About Dopamine
In a similar report, Your Psychology specified that Calipari underscored that these data are rewriting facts about dopamine, including what it's encoding within the brain, not to mention the manner it is driving behavior.
This is incredibly essential as dopamine is dysregulated in a disorder like Parkinson's disease, as well as in almost every psychiatric disease such as anxiety, depression, addiction, and schizophrenia, among others.
Understanding what such dopamine deficiency means will be crucial in understanding the symptoms of patients and developing better evidence-based treatments for these illnesses.
Related information about dopamine is shown on Alila Medical Media's YouTube video below:
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