Recent bioelectric frameworks propose that aging may arise, in part, from a progressive loss of morphostatic control, positioning endogenous electrical signaling as a key regulator of anatomical organization. This perspective has provided important insights into development, regeneration, and large-scale tissue patterning. However, its applicability to complex, post-mitotic systems, particularly the human neuromuscular system, remains incompletely characterized. In this paper, we examine the extent to which bioelectric models can account not only for structural organization but also for the restoration of functional neural execution. We argue that current frameworks primarily address tissue-level morphostasis while underrepresenting the fast, time-dependent neurophysiological processes required for coordinated motor behavior. These processes include motor neuron firing dynamics, temporal and spatial summation, persistent inward currents (PICs), neuromodulatory gain control, network-level synchronization (common drive), and experience-dependent motor engrams. We highlight a fundamental multi-scale distinction between slow, large-scale bioelectric gradients involved in pattern formation and the millisecond-scale, spatially precise signaling required for neural execution. While bioelectric interventions may contribute to restoring anatomical integrity or baseline electrophysiological states, they do not, on their own, provide established mechanisms for reconstructing the dynamic and learned neural processes underlying real-world motor function. Rather than rejecting bioelectricity as a contributing factor in aging, we propose that it represents one layer within a broader, multi-scale system spanning structural, cellular, and network-level dynamics. A comprehensive model of aging and functional recovery must therefore integrate morphostatic regulation with the mechanisms governing neural execution and experience-dependent plasticity. We conclude that future research should explicitly investigate how bioelectric interventions interface with, support, or constrain the restoration of time-dependent neural dynamics. Addressing this gap is essential for evaluating the extent to which bioelectric approaches can contribute to meaningful functional rejuvenation in complex biological systems
Tony Ruggia (Wed,) studied this question.