Peripheral nerve repair is usually framed as a problem of guidance, support, and growth promotion, yet successful regeneration may also require a distributed process of local exploration, route selection, and stabilization. This hypothesis paper proposes a stigmergic systems framework for neuroregeneration inspired by ant-colony construction and collective path optimization. The central claim is that nerve repair can be understood and engineered as a staged process in which cells and axons write transient local traces into the lesion environment, multiple routes are explored in parallel, productive routes are selectively reinforced, unproductive routes are allowed to decay, and functionally successful pathways are progressively consolidated. In this framework, “traces” are not literal insect pheromones but locally persistent, decaying state variables in the regenerative milieu, including biochemical, mechanical, electrical, and structural modifications that bias subsequent cellular and axonal decisions. The paper synthesizes existing observations from Schwann-cell migration, axonal sprouting, extracellular matrix remodeling, growth-factor signaling, and bioengineered guidance scaffolds into a single systems-level hypothesis. The proposed framework is intended primarily for peripheral nerve repair, with only cautious extension to selected central nervous system settings. The main contribution is not the claim of a wholly new biological mechanism, but an explicit integrative architecture for thinking about adaptive nerve repair as distributed search plus selective reinforcement. This architecture yields testable design implications for regenerative biomaterials, multichannel nerve conduits, dynamic cue presentation, and computational simulation. Specifically, it predicts that regenerative outcomes may improve when lesion environments are engineered to support temporary route marking, controlled competition among candidate paths, and gradual stabilization of functionally validated trajectories. This preprint is offered as a hypothesis-generating conceptual framework intended to support future computational, biomaterials, and experimental studies in neuroregeneration.