One of the remarkable characteristics of the brain is its ability to adapt. Brains undergo constant changes, at various time scales, in order to adapt to their surroundings. The functional abilities of our brain are the result of millions of years of evolution, years of neural development, and decades of lifelong learning. Thus, comprehending the brain requires a thorough understanding of its adaptation processes.
Our research in the SNAIL focuses specifically on the functional properties of the visual system. We aim to explore how neural development and lifelong perceptual learning shape the visual system, as well as how evolution has influenced the visual systems of various species. To answer these questions, we develop an algorithmic understanding of how visual experiences and ecological conditions impact the visual system and how they affect our perceptual and visuomotor abilities.
With this goal in mind, we adopt a "NeuroAI" approach, which involves a mutual exchange of knowledge between neuroscience and Artificial Intelligence (AI). On one hand, we employ Artificial Neural Networks and deep learning methods to construct theories on visual development and learning in the brain. On the other hand, we utilize our deep learning-based understanding of brain development and learning to devise novel approaches for constructing AI systems that are more closely aligned with human behavior. Through this ongoing interaction between neuroscience and AI, a thriving ecosystem can be created, leading to a more profound understanding of brain function and the development of better, more human-like AI systems.