The article discusses the challenges and opportunities in developing a neuroscience of natural behavior. Traditional systems neuroscience has relied on simplified laboratory settings to study neural mechanisms, but this approach limits our understanding of the complexity of natural behavior. Recent technological advances, such as wireless recording and automated behavior quantification, enable studies in more naturalistic settings. However, interpreting neural data in these contexts is challenging due to the complexity and variability of natural behavior. Classic studies often controlled variables to interpret neural activity, but in natural settings, variables may not be systematically sampled or may covary, making it difficult to dissociate them. Data-driven approaches can identify patterns of covariation but may not reveal functional principles. Therefore, new theories and hypotheses are needed to explain natural behavior. The article emphasizes the need to revise theoretical frameworks to better address the challenges of natural behavior. It suggests a stepwise approach, gradually moving from constrained to more naturalistic settings while maintaining interpretability. Virtual reality paradigms allow for controlled studies of natural behavior. The article also highlights the importance of integrating sensory and motor functions in natural behavior, as well as the role of evolutionary perspectives in understanding neural mechanisms. It argues that the brain is not just an information processor but a control system that continuously interacts with the environment. The article concludes that developing a neuroscience of natural behavior requires a multidisciplinary approach, combining insights from neuroethology, ecological psychology, and evolutionary biology. This approach allows for the development of theories that are more ecologically valid and can explain the complexity of natural behavior.The article discusses the challenges and opportunities in developing a neuroscience of natural behavior. Traditional systems neuroscience has relied on simplified laboratory settings to study neural mechanisms, but this approach limits our understanding of the complexity of natural behavior. Recent technological advances, such as wireless recording and automated behavior quantification, enable studies in more naturalistic settings. However, interpreting neural data in these contexts is challenging due to the complexity and variability of natural behavior. Classic studies often controlled variables to interpret neural activity, but in natural settings, variables may not be systematically sampled or may covary, making it difficult to dissociate them. Data-driven approaches can identify patterns of covariation but may not reveal functional principles. Therefore, new theories and hypotheses are needed to explain natural behavior. The article emphasizes the need to revise theoretical frameworks to better address the challenges of natural behavior. It suggests a stepwise approach, gradually moving from constrained to more naturalistic settings while maintaining interpretability. Virtual reality paradigms allow for controlled studies of natural behavior. The article also highlights the importance of integrating sensory and motor functions in natural behavior, as well as the role of evolutionary perspectives in understanding neural mechanisms. It argues that the brain is not just an information processor but a control system that continuously interacts with the environment. The article concludes that developing a neuroscience of natural behavior requires a multidisciplinary approach, combining insights from neuroethology, ecological psychology, and evolutionary biology. This approach allows for the development of theories that are more ecologically valid and can explain the complexity of natural behavior.