Capacity and energy cost of information in biological and silicon photoreceptors

We outline a theoretical framework to analyze information processing in bio logical sensory organs and in engineered microsystems. We employ the mathem atical tools of communication theory and model natural or synthetic physica l structures as microscale communication networks, studying them under phys ical constraints at two different levels of abstraction. At the functional levels we examine the operational and task specification. while at the phys ical level, we examine the material specification and realization. Both lev els of abstraction are characterized by Shannon's channel capacity as deter mined bi, the channel bandwidth, the signal power, and the noise power he l ink between the functional level and the physical level of abstraction is e stablished through models for transformations on the signal, physical const raints on the system, and noise that degrades the signal. As a specific example, we present a comparative study of information capaci ty (in bits per second) versus energy cost of information (in joules per bi t) in a biological and in a silicon adaptive photoreceptor The communicatio n channel model for each of the two systems is a cascade of linear bandlimi ting sections followed by additive noise. We model the filters and the nois e from first principles whenever possible and phenomenologically otherwise. The parameters for the blowfly model are determined from biophysical data available in the literature. and the parameters of the silicon model are de termined from our experimental data. This comparative study is a first step toward a fundamental and quantitativ e understanding of the tradeoffs between system performance and associated costs such as size, reliability, and energy requirements for natural and en gineered sensory microsystems.