Arithmetic and neural circuits underlying dopamine prediction errors - Naoshige Uchida

Stanford Neurosciences Institute Seminar Series Presents

Remarkable homogeneity and diversity in dopamine signals

Naoshige Uchida, Ph.D

Professor in the Deparment of Molecular and Cellular Biology, Harvard University

Host: Kevin Bieri (Malenka & Luo Lab)

Abstract

It has been proposed that dopamine neurons in the midbrain signal reward prediction errors, that is, the discrepancy between actual and expected reward (Schultz et al., 1997; Bayer and Glimcher, 2005). These signals resemble error signals used to train computers in machine learning or artificial intelligence.  However, the mechanism underlying this calculation in the brain remains unknown. To probe how dopamine neurons calculate reward prediction error, we have developed a mouse model that allows us to combine electrophysiology in behaving animals with emerging molecular and genetic techniques (Cohen et al., 2012). In this talk, I will discuss some of the on-going works to dissect the nature of reward prediction error computations and its underlying mechanisms.