Professor of Neuroeconomics and Decision Neuroscience
University of Zurich
Dazed and confused? Neuro-computational origins of variability in goal-directed behavior
Goal-directed choices can vary strongly across time, even when the choice options remain constant. Classical behavioral choice models from psychology and economics subsume this variability in unspecific noise terms that have no clearly defined mental basis. In this talk, I propose that the variability of goal-directed choices can emerge naturally from the probabilistic nature of value computations instantiated by neuronal populations in the ventro-medial prefrontal cortex, and by the properties of the computations by which these values are used to infer the preferences guiding our overt choices. I will first show that distributed patterns of neural activity in the vmPFC, as measured with fMRI, contain information about probability distributions over stimulus values and that this probabilistic information can be used to derive estimates of both the preferences themselves and of the associated uncertainty. I will then present a biologically-inspired model of these computations that allows organisms to infer their preferences, in line with constraints imposed by the environment and the brain’s limited capacity for information processing. This model accurately predicts the outcome, response speed, and variability of preference-based decisions and accounts for illusory distortions of preferences and confidence ratings. Together, our data establish that neuro-computational mechanisms established for perceptual systems may also underlie value-based choices; these shared computational mechanisms may allow humans to optimally combine multiple sources of information and may pave the way for mechanistic explanations of puzzling distortions often observed in economic choices.
The talk will begin at 12:00pm. A pizza lunch will be served at 11:45am.