PFC interaction

Dynamic routing of choice-related signals in the prefrontal cortex

Neurons in the prefrontal cortex process multiple types of signals related to the animal’s recent experience and incoming sensory signals during decision making. For further details, see Donahue and Lee (2015).

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graphic task 2018

Prefrontal cortex and reinforcement learning

Speed of leaning increases when the environment becomes more volatile.¬† Similarly, activity in the primate prefrontal cortex changes according to the volatility of the animal’s environment. For further details, refer to Massi et al. (2018).

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RL deviation

Counter-exploitative Strategies during Competitive Games

Choices during a computer-simulated matching pennies task sometimes deviate from the predictions of model-free reinforcement learning algorithm, reflecting  counter-exploitative strategies. Neuronal activity in the medial prefrontal cortex predicts such deviations.  For more details, see Seo et al. (2014).

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Our lab studies the brain mechanisms of decision making and reinforcement learning. We are particularly interested in how the brain flexibly switches among different decision-making strategies. For example, we can choose our response by incrementally adjusting the estimates of expected outcomes through experience, or by relying on our memory of specific events we experienced in the past. We seek to understand the mechanisms that enable us to decide which strategy might work best. In addition, we are also interested in how the brain exploits temporal regularities in the environment, and how different types of numerical information, such as probably and magnitude, are represented and transformed to guide willful and intelligent behaviors.

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