The NERD model: reflex circuit dysfunction as a systems-level driver of persistent post-concussion symptoms

NERD模型:反射回路功能障碍是持续性脑震荡后症状的系统级驱动因素

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Abstract

Persistent post-concussive symptoms are often attributed to diffuse cortical dysfunction, yet this perspective may overlook key systems-level mechanisms. We propose a conceptual framework in which dysfunction arises from the dynamic interplay among five functional nodes: the sensory interface, reflex-brain stem hub, cerebellar module, basal ganglia-thalamic modulator, and cerebral cortex. Grounded in clinical observation and systems-level dynamic modeling, this framework treats the brain as a time-evolving control network that processes inputs, integrates them across hierarchical nodes, and generates adaptive or maladaptive outputs. Subcortical reflex circuits serve as critical nodes in the sensorimotor network, coordinating posture, orientation, and autonomic tone, and are modulated by cortical and thalamic systems. Injury to any of these nodes - or to the connections between them - can disrupt reflex control, distort afferent-efferent signaling, and compromise thalamocortical integration. The cerebellum calibrates predictive timing and coordination, while the basal ganglia-thalamic complex regulates gain and context-dependent gating. The cerebral cortex integrates intention, perception, and prediction to shape voluntary behavior and modulate reflex sensitivity. Reafferent feedback continuously updates the system, creating a dynamic loop of adaptation or maladaptation. Though this model has been applied clinically to guide early intervention, it remains a theoretical framework, untested by formal mathematical modeling or rigorous experimental validation. We offer it as a systems-level model that reframes post-concussive dysfunction as a network-level disorder, with reflex disintegration as a central, actionable mechanism.

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