Larval zebrafish demonstrate sophisticated energy-optimization algorithms in their neural motor circuits, selectively modulating movement patterns to maximize prey capture while minimizing metabolic expenditure during hunting sequences. The research quantifies how developing neural networks balance energetic trade-offs in real-time motor decision-making. This finding extends our understanding of how energy constraints fundamentally shape neural computation and behavioral optimization across species. The metabolic efficiency principles observed in zebrafish hunting circuits likely reflect conserved neural mechanisms present in more complex vertebrate brains, including humans. For longevity-focused adults, this research illuminates how energy-efficient neural processing might influence cognitive aging and motor function preservation. The study suggests that maintaining metabolically optimized neural circuits could be crucial for sustained brain health, particularly in motor control systems that govern daily physical activities. However, the translation from larval fish to human neural aging requires significant extrapolation. The research remains primarily foundational, offering insights into evolutionary optimization principles rather than direct therapeutic applications. Understanding these energy-economy neural principles could eventually inform strategies for maintaining efficient brain function and motor control throughout the human lifespan.