Critical Learning Periods for Multisensory Integration in Deep Networks
Michael Kleinman, Alessandro Achille, Stefano Soatto · COSYNE 2023
We show that the ability of a neural network to integrate information from diverse sources hinges critically on being exposed to properly correlated signals during the early stages of learning. Interfering with the learning process during this initial stage can permanently impair the development of a skill, both in artificial (Achille et al., 2019) and biological systems where the phenomenon is known as a critical learning period (Wiesel, 1982). Critical periods have since been described in many different species and sensory organs: for example, barn owls originally exposed to misaligned audit
Sun, Mar 12, 2023