Abstract:
Foundational models in Occupational Therapy (OT), while conceptually rich, have historically lacked the mathematical formalism and dynamic explanatory power necessary to fully capture the emergent, non-linear complexity of human occupation. This paper addresses these limitations by introducing the Heptadic Framework for Neuro-computational Occupational Dynamics (H-NOD), a novel paradigm that synthesizes occupational science with principles from computational neuroscience and dynamical systems theory. The H-NOD framework posits that occupation is not a discrete activity but a continuous trajectory within a high-dimensional “Occupational State Space,” the topography of which is determined by an individual’s unique neural architecture, or connectome. The dynamics within this space are characterized by the convergence of occupational states toward one of seven fundamental, universally available “attractor states”—stable, preferred modes of neuro-cognitive engagement. These attractors, defined by the dominant activity of large-scale brain networks, provide a unified neurobiological basis for diverse occupational phenomena, including sensory processing, creative ideation, and habituated performance. By modeling dysfunction as entrapment within maladaptive attractors and therapeutic change as a targeted perturbation that facilitates a phase transition to a more functional state, H-NOD offers a unifying, first-principles approach to understanding occupational behavior. This framework bridges the gap between abstract OT theory and its underlying neurobiological mechanisms, providing a new, generative language for clinical reasoning and future research.
Yıldırım, E. (2025). The Heptadic Framework for Neuro-computational Occupational Dynamics (H-NOD): A Synthesis of Occupational Science and Complex Systems Theory. Zenodo. https://doi.org/10.5281/zenodo.17057813
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