Errors drive the evolution of biological signalling to costly codes.

Area of Science:

• Evolutionary biology
• Information theory
• Neuroscience

Background:

• Biological signaling typically favors cost reduction as an evolutionary advantage.
• Recent experiments indicate a shift towards high-cost signals with underutilization of low-cost signals in biological communication.

Purpose of the Study:

• To derive a theory for efficient biological signaling that incorporates both errors and costs.
• To explain the observed shift towards higher-cost signals and underutilization of low-cost signals.

Main Methods:

• Theoretical derivation of an efficient signaling model.
• Analysis of signal usage statistics under error constraints.
• Comparison of theoretical predictions with experimental data from visual cortex neurons.

Main Results:

• Errors in translating biological states to signals can necessitate a shift to higher-cost signals, acting as a quality control mechanism.
• The statistical structure of signal usage is predicted to follow a generalized Boltzmann distribution.
• This distribution penalizes costly and error-sensitive signals, featuring an exponential tail for cost efficiency and underutilization of low-cost signals to maintain quality.

Conclusions:

• The theory provides a quantitative explanation for the observed signal cost distributions in biological systems.
• Signal errors play a crucial role in shaping the evolution of signaling strategies, favoring quality over minimal cost.
• The findings have implications for understanding communication efficiency in biological systems, including neural signaling.