Resource limitations induce phase transitions in biological information processing

Biological information processing exhibits remarkable diversity across different organisms, which is presumably shaped by evolutionary optimization under limited resources. Starting from simple memoryless responses, more complex memory-based strategies may have evolved as resources became more available. In this Letter, we investigate minimal models of biological information processing under resource limitations by applying an optimal control technique proposed in [Tottori and Kobayashi, ]. We find that resource limitations such as sensing reliability, intrinsic stochasticity, and energy cost induce discontinuous phase transitions between memoryless and memory-based strategies, even though the minimal models fall within the standard linear-quadratic-Gaussian class. Moreover, these transitions can be nonmonotonic: Optimal information processing initially shifts from memoryless to memory-based strategies as sensing reliability increases, but then reverts to memoryless strategies if it increases further. Our results suggest that the complexity of biological information processing may be an evolvable trait that can switch back and forth between distinct strategies in a punctuated manner.