Signal weighting as an organizing principle of adaptive systems

Current frameworks in biology, centred on replication, variation, and selection, have provided powerful explanations for evolutionary change. However, they do not fully account for how adaptive systems determine relevance in context, nor how stable, integrated behaviours emerge across interacting components. Across diverse biological domains - including immune recognition, host-microbiome interactions, and neural systems - adaptive behaviour depends on the capacity to filter, prioritise, and refine signals in response to feedback. Here we propose that this process, which we term signal weighting, constitutes an organizing principle of adaptive systems. Signal weighting describes the dynamic assignment of relevance to incoming signals through iterative filtering, amplification, and suppression, enabling systems to adjust their responses in context. This logic is evident in immune pattern recognition, where signals are selectively reinforced or attenuated to maintain functional balance, and in microbial ecosystems, where community structure reflects continuous feedback between environmental inputs and metabolic outputs. Importantly, adaptive systems rarely operate in isolation. When multiple signal-weighting processes interact, their coupling can stabilize shared behaviours, producing coherent higher-order organization. Such interactions are observed in host-microbiome systems, where immune and microbial processes reciprocally shape one another, maintaining functional stability despite ongoing perturbation. By reframing adaptation in terms of signal weighting, this perspective shifts emphasis from replication alone to the underlying processes through which systems filter, interpret, and stabilise relevant information. By identifying similar weighting architectures across biological substrates and scales, this framework highlights a recurrent organisational principle underlying adaptive behaviour and provides a mechanistic basis for understanding the emergence of complexity in living systems.