The article discusses the structure-function partitioning of cognitive-emotional brain networks, emphasizing the importance of neural field theories and physiological constructs in understanding brain dynamics. It critiques Pessoa's use of 2D graph network theory, arguing that it fails to capture the dynamic and complex nature of brain networks. The author highlights the significance of weak-to-strong structure-function correlations and the role of neuronal plasticity in shaping brain networks. The article introduces neural field theories, which model the evolution of brain networks between classical and quantum computational phases, and emphasizes the need for network partitioning to achieve optimal cognitive-emotional functionality. It also explores the scalability of local bidirectional metaplasticity and the impact of control parameters on network behavior. The article concludes by discussing the continuum limits of hybrid classical-quantum neural fields and their implications for cognitive-emotional network functions.The article discusses the structure-function partitioning of cognitive-emotional brain networks, emphasizing the importance of neural field theories and physiological constructs in understanding brain dynamics. It critiques Pessoa's use of 2D graph network theory, arguing that it fails to capture the dynamic and complex nature of brain networks. The author highlights the significance of weak-to-strong structure-function correlations and the role of neuronal plasticity in shaping brain networks. The article introduces neural field theories, which model the evolution of brain networks between classical and quantum computational phases, and emphasizes the need for network partitioning to achieve optimal cognitive-emotional functionality. It also explores the scalability of local bidirectional metaplasticity and the impact of control parameters on network behavior. The article concludes by discussing the continuum limits of hybrid classical-quantum neural fields and their implications for cognitive-emotional network functions.