Neural circuitry mechanisms in decision-making

The brain is the exclusive organ that makes decisions for humans and the society. In this thesis, I will discuss recent advances in the understanding of neuroscientific mechanisms in decision-making. Decision-making is not a new topic in the human history, but it has existed for thousands of years. We made numerous decisions over centuries, and the consequences of those decisions transformed the landscape of the Earth, established the norms for our society, and revolutionized our way of thinking. To understand the concepts and frameworks for decision-making, I will review significant intellectual advances in the history, start with several simple enough models to describe and predict decisionmaking behaviors. However, the models, concepts, and logical deduction do not provide enough understanding of the decision-making process. We should also aware limitations, which determine our choice processes and outcomes, such as how much information we have, how much cognitive power we can put into a problem. After the established the models that sufficiently contain the errors and limitations of decision-making, the central question is to understand the brain, which operates the whole process. As the brain is specialized into functional regions, it is easier to build hypothesis in decision-making process if we conceptually break down the decision-making process into discrete stages. Firstly, attention is the foremost important mechanism controls our actions and choices. Only with attention allocated to the problem, one can then represent the problem to related brain areas, mobilize memory and the affective system to retrieve internal status, start evaluating different choices, plan and take action, reevaluate the outcome and update the original memory and representation of values. To further dissect the decisionmaking mechanism in the brain, particularly in this thesis, we examined and discussed neural circuits that are regulated by local interneurons and long-range neuromodulators. Moreover, such knowledge can be robustly translated into an understanding of various types of mental disorders. In this thesis, three studies are included to illustrate how different neural circuits could alter animals' decision-making process and performance. In Paper I, the prefrontal fast-spiking interneurons were recorded and manipulated in a task measuring a goal-directed behavior and top-down attention. The neuronal activities of fast-spiking cells in the medial prefrontal cortex were significantly regulated during the attentional process, and such pattern defined the firing of the principal neurons with a phase-locking mechanism. We further showed enhanced gamma synchrony characterized the successful allocation of attention. Moreover, modulation of gamma synchrony using optogenetics can significantly change the animals' performance in top-down attention. In Paper II, we investigated the functions of fast-spiking NMDA glutamate receptors in depressive-like behavior. Using a genetically modified animal model, we compared the phenotypes between the fast-spiking NMDA receptor knockout animals and controls. There was no significant difference between two groups in response to non-competitive NMDA receptor antagonist in expressing depressive-like symptoms or in anhedonia. In Paper III, we investigated the role of the long-range modulatory serotonergic system in impulsive behaviors. Activation of the ascending serotonergic population with optogenetics slightly alleviate the level of impulsiveness in both impulsive action and impulsive choice. Conversely, optogenetic inhibition of the ascending serotonergic population significantly increased impulsive action and impulsive choice. Furthermore, using optical calcium imaging, our results illustrated that the neuronal activities of the ascending serotonergic population strongly responded to the delivery of reward. In summary, the work of this thesis provides a further understanding and new insights of functional roles of particular neuronal subpopulations in different discrete stages of decision-making