TY - JOUR A1 - Axenie, Cristian T1 - Antifragile control systems in neuronal processing: a sensorimotor perspective T2 - Biological Cybernetics N2 - The stability–robustness–resilience–adaptiveness continuum in neuronal processing follows a hierarchical structure that explains interactions and information processing among the different time scales. Interestingly, using “canonical” neuronal computational circuits, such as Homeostatic Activity Regulation, Winner-Take-All, and Hebbian Temporal Correlation Learning, one can extend the behavior spectrum towards antifragility. Cast already in both probability theory and dynamical systems, antifragility can explain and define the interesting interplay among neural circuits, found, for instance, in sensorimotor control in the face of uncertainty and volatility. This perspective proposes a new framework to analyze and describe closed-loop neuronal processing using principles of antifragility, targeting sensorimotor control. Our objective is two-fold. First, we introduce antifragile control as a conceptual framework to quantify closed-loop neuronal network behaviors that gain from uncertainty and volatility. Second, we introduce neuronal network design principles, opening the path to neuromorphic implementations and transfer to technical systems. Y1 - 2025 UR - https://opus4.kobv.de/opus4-ohm/frontdoor/index/index/docId/3328 SN - 1432-0770 VL - 119 IS - 2-3 PB - Springer Nature ER -