Our Research Approach
How do newborns learn to perceive and understand the world? Although philosophers and psychologists have puzzled over the origins of the mind for centuries, two major barriers have hindered progress. First, humans can't be raised in strictly controlled environments from birth, so it has not been possible to examine how specific experiences shape newborn minds. Second, newborn humans can’t be tested continuously for long periods of time, so it has not been possible to examine — with high precision — how perception and cognition emerge in newborn brains.
To overcome these barriers, we turn to controlled-rearing studies of newborn chicks. We use newborn chicks as an animal model because they are uniquely suited for studying the earliest stages of visual learning. Unlike commonly used animal models in psychology (e.g., rats, pigeons, and monkeys), chickens are a precocial species (mobile in the first day of life without the need for parental support) and can be raised in strictly controlled environments immediately after hatching. Chicks and humans also process sensory input using homologous neural circuits, and their brains conform to the same organizational principles.
To study the origins of perception and cognition in chicks, our lab has developed a variety of automated controlled-rearing methods. These methods allow newborn chicks to be raised in strictly controlled virtual environments from the onset of vision. Using automated image-based tracking software, we record all of the chicks’ behavior (24/7), providing a complete digital record of each newborn chick's behavior over their first few weeks of life. As a result, we can measure early emerging perceptual and cognitive abilities with an unprecedented degree of precision. This video will take you on a short virtual tour of our lab to see our controlled-rearing chambers.
Our goal is to develop quantitative models of the core learning algorithms in newborn brains. For each controlled-rearing experiment, we create “digital twin” experiments for testing the learning abilities of autonomous artificial agents (models). The artificial agents receive only pixels as input (akin to the retinal images received by newborn chicks) and are raised in virtual environments that simulate the learning conditions of the chicks. By raising newborn animals and artificial agents in the same environments, we can compare their learning abilities and build “runnable” models of newborn brains. To promote a community-wide effort to formalize the core learning algorithms in brains, this testbed is available at: https://origins.luddy.indiana.edu/
