Abstract

This symposium addresses a fundamental challenge in neuroscience and AI: understanding and validating the computational principles that enable autonomous behavior across biological and artificial systems. The speakers bring complementary expertise in theoretical neuroscience, neural dynamics, and embodied intelligence to examine this question from multiple angles.

Dr. Aran Nayebi will present work on reverse-engineering algorithmic principles of animal cognition and their application to autonomous robots, providing a crucial bridge between biological and artificial systems. Dr. James Whittington will discuss theoretical frameworks for understanding how neural systems build world models and representations. Mia Kvalsund will explore the benefits of active sensing in artificial agents, offering insights into sensori-motor computational mechanisms.

Together, these talks will highlight emerging approaches for validating computational principles across biological and artificial systems while critically examining the challenges and opportunities in translating between them. The symposium aims to foster discussion about how theoretical frameworks, empirical findings, and practical applications can inform each other to advance our understanding of neural computation.