Building newborn minds in virtual worlds
Abstract: What are the origins of high-level vision: Is this ability hardwired by genes or learned during development? Although researchers have been wrestling with this question for over a century, progress has been hampered by two major limitations: (1) most newborn animals cannot be raised in controlled environments from birth, and (2) most newborn animals cannot be observed and tested for long periods of time. Thus, it has generally not been possible to characterize how specific visual inputs relate to specific cognitive outputs in the newborn brain.
To overcome these two limitations, I recently developed an automated, high-throughput controlled-rearing technique. This technique can be used to measure all of a newborn animal’s behavior (9 samples/second, 24 hours/day, 7 days/week) within strictly controlled virtual environments. In this talk, I will describe a series of controlled-rearing experiments that reveal how one high-level visual ability—invariant object recognition—emerges in the newborn brain. Further, I will show how these controlled-rearing data can be linked to models of visual cortex for characterizing the computations underlying newborn vision. More generally, I will argue that controlled rearing can serve as a critical tool for testing between different theories and models, both for developmental psychology and computational neuroscience.
Organizer: Elizabeth Spelke Joshua Tenenbaum
