Elucidation of the neural mechanisms for reward-based learning and decision making

ResearcherTomohiko YoshizawaAssistant Professor

Individuals can learn new behaviors in unfamiliar environments by exploring and memorizing sensory cues or actions that lead to good or bad outcomes. For instance, if you touch a hot oven, you very quickly learn not to do it again. Learning by trial-and-error, which can yield positive or negative consequences, is known as reinforcement learning.

Neuroscientists know that a part of the forebrain called basal ganglia plays an important role in reinforcement learning. A major part of the basal ganglia, the striatum, is composed of a patchwork of two types of tissue: the striosome and the matrix. Currently, I am trying to clarify the role of striosome/matrix on reinforcement learning by using in vivo calcium imaging, electrophysiological recording and optogenetics.

Methods: in vivo calcium imaging, 32ch electrophysiological recording, restraint operant test etc.

Tomohiko Yoshizawa
Assistant Professor

Keyword Striatum. Striosome/Matrix, Reinforcement Learning, Area postrema
Fields Life sciences / Neuroscience - general /
Life sciences / Oral medicine /
Project
  • 2020FY