Efficiency and complexity in neural coding
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Updated: Oct 4, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
Published on: March 2, 2015
1Department of Zoology, University of Cambridge, UK.
Abstract:
Neural coding in the retina and lamina of fly compound eyes is amenable to detailed anatomical, physiological and theoretical analysis. This approach shows how identified cell signalling systems are optimized to maximize the transmission of information. Optimization reveals three familiar constraints, noise, saturation and bandwidth, and shows how coding can minimize their effects. Experiments reveal a fourth constraint, metabolic cost, whose properties favour the distribution of information among multiple pathways. The advantages of distributed codes will be offset by increasing complexity and the build up of noise. The optimization of coding in fly retina suggests that both noise and complexity will be reduced by matching each step in the system's operations to the input signal, and to the logical requirements of the network's ultimate function, pattern processing. This line of argument suggests tightly organized networks, laid out that information flows freely and independently, yet patterned so that the necessary contacts and transactions are made quickly and efficiently.
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