Adaptive Neuroregulation Ontology (ANO)

This addresses the gap in existing neurocognitive classification systems, which often rely on static categorical diagnostic frameworks rather than dynamic process-level models. The proposed computational framework introduces a state-space approach to classify and monitor neurocognitive regulatory states by integrating the activation dynamics and regulatory effectiveness. It quantifies neurocognitive function as the interplay between activation levels and regulatory control capacity, which is modeled as dynamically coupled dimensions. Multimodal inputs are transformed into coherence indices (reflecting functional integration), fragmentation measures (capturing coordination inconsistency), and decay metrics…