Neuromorphic computing stands out as a pivotal solution for overcoming the energy efficiency limitations inherent in conventional computing frameworks, thanks to its remarkable parallel processing capabilities and minimal power requirements. Yet, the transition of this computing model from rigid chips to adaptable, wearable fiber-shaped devices poses a significant hurdle in the development of next-generation, highly integrated, and intelligent wearable textile systems. Fiber-based electrochemical iontronic synapses, which integrate ion movement with electron flow, can emulate the information-processing mechanisms of biological synapses at low voltages, laying a hardware groundwork for distributed, wearable brain-inspired computing. However, existing research encounters several obstacles: subpar rectification ratios compromise signal integrity, energy consumption vastly surpasses that of biological synapses, functional integration remains constrained, and the inability to prevent crystallization at low temperatures hinders operation in cold environments.