Prior knowledge affects the way we interpret incoming sensory signals, both based on long-term learning (memory colors), and short-term learning (statistical priors). In my own research, I have discovered that prior knowledge about object identity affects the way we perceive their colors (see e.g Olkkonen, Hansen, & Gegenfurtner, 2008 ). More recently, I found that prior knowledge acquired on the shorter term also affects color appearance in delayed color matches ( Olkkonen, McCarthy, & Allred, 2014).

The effect of long-term or short-term memory processes on color appearance are not explained by current models of color perception or memory, but fit well in a probabilistic inference framework based on a Bayesian ideal observer. A Bayesian observer estimates the external cause of an incoming sensory signal by combining the sensory evidence with prior information about the world. Together with Toni Saarela and Sarah Allred, I have implemented a Bayesian model observer that produces similar interactions between perceptual constancy and short-term memory for lightness that we observed recently in human observers for both lightness and hue (Olkkonen & Allred, 2014 ; Olkkonen, Saarela, & Allred, in prep (OSA 2014 abstract))). My next goal is to implement this model in full-color scenes, and test the model with a new, independent data set.

Principal investigator: Maria Olkkonen