Integrating Vision: From Neuroscience to Artificial Intelligence

Abstract. This review article explores the complex interplay between neuroscience and artificial intelligence, focusing on vision processing and its applications. It starts by outlining the biological basis of vision, delving into how visual information is processed and encoded in the brain. The discussion then transitions to artificial intelligence, particularly machine vision, highlighting the advancements and technologies that mimic biological processes. A critical analysis compares how visual information is utilized in both biological organisms and artificial systems, with an emphasis on cognitive functions and neural encoding. The challenges of integrating vision across various sensory modalities are examined, underscoring the technological and cognitive limitations currently faced. The review culminates by identifying potential research paths aimed at closing the gap between neuroscience and AI. This involves enhancing the understanding and functionality of vision in multisensory contexts, striving to foster a more comprehensive approach to artificial intelligence that mirrors the complexity of human perception.